Relevant bibliographies by topics / Mixed frequency time series

Academic literature on the topic 'Mixed frequency time series'

Author: Grafiati
Published: 10 December 2022
Last updated: 29 January 2023

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Journal articles on the topic "Mixed frequency time series"

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Götz, Thomas B., Alain Hecq, and Jean-Pierre Urbain. "Forecasting Mixed-Frequency Time Series with ECM-MIDAS Models." Journal of Forecasting 33, no. 3 (March 3, 2014): 198–213. http://dx.doi.org/10.1002/for.2286.

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Ghysels, Eric, and J. Isaac Miller. "Testing for Cointegration with Temporally Aggregated and Mixed-Frequency Time Series." Journal of Time Series Analysis 36, no. 6 (March 9, 2015): 797–816. http://dx.doi.org/10.1111/jtsa.12129.

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Miller, J. Isaac. "Conditionally Efficient Estimation of Long-Run Relationships Using Mixed-Frequency Time Series." Econometric Reviews 35, no. 6 (October 20, 2014): 1142–71. http://dx.doi.org/10.1080/07474938.2014.976527.

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Seong, Byeongchan. "Smoothing and forecasting mixed-frequency time series with vector exponential smoothing models." Economic Modelling 91 (September 2020): 463–68. http://dx.doi.org/10.1016/j.econmod.2020.06.020.

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Tank, A., E. B. Fox, and A. Shojaie. "Identifiability and estimation of structural vector autoregressive models for subsampled and mixed-frequency time series." Biometrika 106, no. 2 (April 8, 2019): 433–52. http://dx.doi.org/10.1093/biomet/asz007.

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Summary Causal inference in multivariate time series is challenging because the sampling rate may not be as fast as the time scale of the causal interactions, so the observed series is a subsampled version of the desired series. Furthermore, series may be observed at different sampling rates, yielding mixed-frequency series. To determine instantaneous and lagged effects between series at the causal scale, we take a model-based approach that relies on structural vector autoregressive models. We present a unifying framework for parameter identifiability and estimation under subsampling and mixed frequencies when the noise, or shocks, is non-Gaussian. By studying the structural case, we develop identifiability and estimation methods for the causal structure of lagged and instantaneous effects at the desired time scale. We further derive an exact expectation-maximization algorithm for inference in both subsampled and mixed-frequency settings. We validate our approach in simulated scenarios and on a climate and an econometric dataset.
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Götz, Thomas B., and Klemens Hauzenberger. "Large mixed-frequency VARs with a parsimonious time-varying parameter structure." Econometrics Journal 24, no. 3 (January 16, 2021): 442–61. http://dx.doi.org/10.1093/ectj/utab001.

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Summary In order to simultaneously consider mixed-frequency time series, their joint dynamics, and possible structural change, we introduce a time-varying parameter mixed-frequency vector autoregression (VAR). Time variation enters in a parsimonious way: only the intercepts and a common factor in the error variances can vary. Computational complexity therefore remains in a range that still allows us to estimate moderately large VARs in a reasonable amount of time. This makes our model an appealing addition to any suite of forecasting models. For eleven U.S. variables, we show the competitiveness compared to a commonly used constant-coefficient mixed-frequency VAR and other related model classes. Our model also accurately captures the drop in the gross domestic product during the COVID-19 pandemic.
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Khiabani, Naser, and Fateme Rajabi. "Modeling with Mixed Frequency Variables: A Review of Recently Extended Methods in Time Series Econometrics." Journal of Planning and Budgeting 24, no. 2 (September 1, 2019): 3–30. http://dx.doi.org/10.29252/jpbud.24.2.3.

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Belovas, Igoris, Leonidas Sakalauskas, Vadimas Starikovičius, and Edward W. Sun. "Mixed-Stable Models: An Application to High-Frequency Financial Data." Entropy 23, no. 6 (June 11, 2021): 739. http://dx.doi.org/10.3390/e23060739.

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The paper extends the study of applying the mixed-stable models to the analysis of large sets of high-frequency financial data. The empirical data under review are the German DAX stock index yearly log-returns series. Mixed-stable models for 29 DAX companies are constructed employing efficient parallel algorithms for the processing of long-term data series. The adequacy of the modeling is verified with the empirical characteristic function goodness-of-fit test. We propose the smart-Δ method for the calculation of the α-stable probability density function. We study the impact of the accuracy of the computation of the probability density function and the accuracy of ML-optimization on the results of the modeling and processing time. The obtained mixed-stable parameter estimates can be used for the construction of the optimal asset portfolio.
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Martínez-Ortiz, Pedro A., and José M. Ferrándiz. "A New Algorithm to Accelerate Harmonic Analysis of Time Series." ISRN Applied Mathematics 2013 (February 11, 2013): 1–8. http://dx.doi.org/10.1155/2013/916731.

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The Lomb periodogram has been traditionally a tool that allows us to elucidate if a frequency turns out to be important for explaining the behaviour of a given time series. Many linear and nonlinear reiterative harmonic processes that are used for studying the spectral content of a time series take into account this periodogram in order to avoid including spurious frequencies in their models due to the leakage problem of energy from one frequency to others. However, the estimation of the periodogram requires long computation time that makes the harmonic analysis slower when we deal with certain time series. Here we propose an algorithm that accelerates the extraction of the most remarkable frequencies from the periodogram, avoiding its whole estimation of the harmonic process at each iteration. This algorithm allows the user to perform a specific analysis of a given scalar time series. As a result, we obtain a functional model made of (1) a trend component, (2) a linear combination of Fourier terms, and (3) the so-called mixed secular terms by reducing the computation time of the estimation of the periodogram.
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FRANCO, Ray John Gabriel, and Dennis S. MAPA. "ANALYZING THE DYNAMICS OF GROSS DOMESTIC PRODUCT GROWTH. A MIXED FREQUENCY MODEL APPROACH." Theoretical and Practical Research in the Economic Fields 5, no. 2 (December 31, 2014): 117. http://dx.doi.org/10.14505/tpref.v5.2(10).01.

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Frequency mismatch has been a problem in time series econometrics. Many monthly economic and financial indicators are normally aggregated to match quarterly macroeconomic series such as Gross Domestic Product when performing econometric analysis. However, temporal aggregation, although widely accepted, is prone to information loss. To address this issue, mixed frequency modelling is employed by using state space models with time-varying parameters. Quarter-on-quarter growth rate of GDP estimates are treated as monthly series with missing observation. Using Kalman filter algorithm, state space models are estimated with eleven monthly economic indicators as explanatory variables. A one-step-ahead forecast for GDP growth rates is generated and as more indicators are included in the model, the predicted values became closer to the actual data. Further evaluation revealed that among the group competing models, using Consumer Price Index (CPI), growth rates of Philippine Stock Exchange Index (PSEi), Exchange Rate, Real Money Supply, Wholesale Price Index (WPI) and Merchandise Exports are the more important determinants of GDP growth and generated the most desirable forecasts (lower forecast errors).
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Dissertations / Theses on the topic "Mixed frequency time series"

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Wohlrabe, Klaus. "Forecasting with mixed-frequency time series models." Diss., lmu, 2009. http://nbn-resolving.de/urn:nbn:de:bvb:19-96817.

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Marsilli, Clément. "Mixed-Frequency Modeling and Economic Forecasting." Thesis, Besançon, 2014. http://www.theses.fr/2014BESA2023/document.

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La prévision macroéconomique à court terme est un exercice aussi complexe qu’essentiel pour la définition de la politique économique et monétaire. Les crises financières récentes ainsi que les récessions qu’ont endurées et qu’endurent aujourd’hui encore, en ce début d’année 2014, nombre de pays parmi les plus riches, témoignent de la difficulté d’anticiper les fluctuations économiques, même à des horizons proches. Les recherches effectuées dans le cadre de la thèse de doctorat qui est présentée dans ce manuscrit se sont attachées à étudier, analyser et développer des modélisations pour la prévision de croissance économique. L’ensemble d’informations à partir duquel construire une méthodologie prédictive est vaste mais également hétérogène. Celle-ci doit en effet concilier le mélange des fréquences d’échantillonnage des données et la parcimonie nécessaire à son estimation. Nous évoquons à cet effet dans un premier chapitre les éléments économétriques fondamentaux de la modélisation multi-fréquentielle. Le deuxième chapitre illustre l’apport prédictif macroéconomique que constitue l’utilisation de la volatilité des variables financières en période de retournement conjoncturel. Le troisième chapitre s’étend ensuite sur l’inférence bayésienne et nous présentons par ce biais un travail empirique issu de l’adjonction d’une volatilité stochastique à notre modèle. Enfin, le quatrième chapitre propose une étude des techniques de sélection de variables à fréquence multiple dans l’optique d’améliorer la capacité prédictive de nos modélisations. Diverses méthodologies sont à cet égard développées, leurs aptitudes empiriques sont comparées, et certains faits stylisés sont esquissés
Economic downturn and recession that many countries experienced in the wake of the global financial crisis demonstrate how important but difficult it is to forecast macroeconomic fluctuations, especially within a short time horizon. The doctoral dissertation studies, analyses and develops models for economic growth forecasting. The set of information coming from economic activity is vast and disparate. In fact, time series coming from real and financial economy do not have the same characteristics, both in terms of sampling frequency and predictive power. Therefore short-term forecasting models should both allow the use of mixed-frequency data and parsimony. The first chapter is dedicated to time series econometrics within a mixed-frequency framework. The second chapter contains two empirical works that sheds light on macro-financial linkages by assessing the leading role of the daily financial volatility in macroeconomic prediction during the Great Recession. The third chapter extends mixed-frequency model into a Bayesian framework and presents an empirical study using a stochastic volatility augmented mixed data sampling model. The fourth chapter focuses on variable selection techniques in mixed-frequency models for short-term forecasting. We address the selection issue by developing mixed-frequency-based dimension reduction techniques in a cross-validation procedure that allows automatic in-sample selection based on recent forecasting performances. Our model succeeds in constructing an objective variable selection with broad applicability
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Pacce, Matías José. "Essays on Business Cycles Fluctuations and Forecasting Methods." Doctoral thesis, Universidad de Alicante, 2017. http://hdl.handle.net/10045/71346.

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This doctoral dissertation proposes methodologies which, from a linear or a non-linear approach, accommodate to the information flow and can deal with a large amount of data. The empirical application of the proposed methodologies contributes to answer some of the questions that have emerged or that it has potentiated after the 2008 global crisis. Thus, essential aspects of the macroeconomic analysis are studied, like the identification and forecast of business cycles turning points, the business cycles interactions between countries or the development of tools able to forecast the evolution of key economic indicators based on new data sources, like those which emerge from search engines.
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Elayouty, Amira Sherif Mohamed. "Time and frequency domain statistical methods for high-frequency time series." Thesis, University of Glasgow, 2017. http://theses.gla.ac.uk/8061/.

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Advances in sensor technology enable environmental monitoring programmes to record and store measurements at high-temporal resolution over long time periods. These large volumes of high-frequency data promote an increasingly comprehensive picture of many environmental processes that would not have been accessible in the past with monthly, fortnightly or even daily sampling. However, benefiting from these increasing amounts of high-frequency data presents various challenges in terms of data processing and statistical modeling using standard methods and software tools. These challenges are attributed to the large volumes of data, the persistent and long memory serial correlation in the data, the signal to noise ratio, and the complex and time-varying dynamics and inter-relationships between the different drivers of the process at different timescales. This thesis aims at using and developing a variety of statistical methods in both the time and frequency domains to effectively explore and analyze high-frequency time series data as well as to reduce their dimensionality, with specific application to a 3 year hydrological time series. Firstly, the thesis investigates the statistical challenges of exploring, modeling and analyzing these large volumes of high-frequency time series. Thereafter, it uses and develops more advanced statistical techniques to: (i) better visualize and identify the different modes of variability and common patterns in such data, and (ii) provide a more adequate dimension reduction representation to the data, which takes into account the persistent serial dependence structure and non-stationarity in the series. Throughout the thesis, a 15-minute resolution time series of excess partial pressure of carbon dioxide (EpCO2) obtained for a small catchment in the River Dee in Scotland has been used as an illustrative data set. Understanding the bio-geochemical and hydrological drivers of EpCO 2 is very important to the assessment of the global carbon budget. Specifically, Chapters 1 and 2 present a range of advanced statistical approaches in both the time and frequency domains, including wavelet analysis and additive models, to visualize and explore temporal variations and relationships between variables for the River Dee data across the different timescales to investigate the statistical challenges posed by such data. In Chapter 3, a functional data analysis approach is employed to identify the common daily patterns of EpCO2 by means of functional principal component analysis and functional cluster analysis. The techniques used in this chapter assume independent functional data. However, in numerous applications, functional observations are serially correlated over time, e.g. where each curve represents a segment of the whole time interval. In this situation, ignoring the temporal dependence may result in an inappropriate dimension reduction of the data and inefficient inference procedures. Subsequently, the dynamic functional principal components, recently developed by Hor mann et al. (2014), are considered in Chapter 4 to account for the temporal correlation using a frequency domain approach. A specific contribution of this thesis is the extension of the methodology of dynamic functional principal components to temporally dependent functional data estimated using any type of basis functions, not only orthogonal basis functions. Based on the scores of the proposed general version of dynamic functional principal components, a novel clustering approach is proposed and used to cluster the daily curves of EpCO2 taking into account the dependence structure in the data. The dynamic functional principal components depend in their construction on the assumption of second-order stationarity, which is not a realistic assumption in most environmental applications. Therefore, in Chapter 5, a second specific contribution of this thesis is the development of a time-varying dynamic functional principal components which allows the components to vary smoothly over time. The performance of these smooth dynamic functional principal components is evaluated empirically using the EpCO2 data and using a simulation study. The simulation study compares the performance of smooth and original dynamic functional principal components under both stationary and non-stationary conditions. The smooth dynamic functional principal components have shown considerable improvement in representing non-stationary dependent functional data in smaller dimensions. Using a bootstrap inference procedure, the smooth dynamic functional principal components have been subsequently employed to investigate whether or not the spectral density and covariance structure of the functional time series under study change over time. To account for the possible changes in the covariance structure, a clustering approach based on the proposed smooth dynamic functional principal components is suggested and the results of application are discussed. Finally, Chapter 6 provides a summary of the work presented within this thesis, discusses the limitations and implications and proposes areas for future research.
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Lundbergh, Stefan. "Modelling economic high-frequency time series." Doctoral thesis, Handelshögskolan i Stockholm, Ekonomisk Statistik (ES), 1999. http://urn.kb.se/resolve?urn=urn:nbn:se:hhs:diva-637.

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Mui, Chi Seong. "Frequency domain approach to time series analysis." Thesis, University of Macau, 2000. http://umaclib3.umac.mo/record=b1446676.

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Terwilleger, Erin. "Multidimensional time-frequency analysis /." free to MU campus, to others for purchase, 2002. http://wwwlib.umi.com/cr/mo/fullcit?p3052223.

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Erkan, Ibrahim. "Mixed Effects Models For Time Series Gene Expression Data." Phd thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613913/index.pdf.

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The experimental factors such as the cell type and the treatment may have different impact on expression levels of individual genes which are quantitative measurements from microarrays. The measurements can be collected at a few unevenly spaced time points with replicates. The aim of this study is to consider cell type, treatment and short time series attributes and to infer about their effects on individual genes. A mixed effects model (LME) was proposed to model the gene expression data and the performance of the model was validated by a simulation study. Realistic data sets were generated preserving the structure of the sample real life data studied by Nymark et al. (2007). Predictive performance of the model was evaluated by performance measures, such as accuracy, sensitivity and specificity, as well as compared to the competing method by Smyth (2004), namely Limma. Both methods were also compared on real life data. Simulation results showed that the predictive performance of LME is as high as 99%, and it produces False Discovery Rate (FDR) as low as 0.4% whereas Limma has an FDR value of at least 32%. Moreover, LME has almost 99% predictive capability on the continuous time parameter where Limma has only about 67% and even it cannot handle continuous independent variables.
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Åsbrink, Stefan E. "Nonlinearities and regime shifts in financial time series /." Stockholm : Economic Research Institute, Stockholm School of Economics [Ekonomiska forskningsinstitutet vid Handelshögsk.] (EFI), 1997. http://www.hhs.se/efi/summary/439.htm.

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Lin, Shinn-Juh. "Modelling high frequency financial time series with trading information." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp02/NQ31160.pdf.

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Books on the topic "Mixed frequency time series"

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Cohen, Leon. Time-frequency analysis. Englewood Cliffs, N.J: Prentice Hall PTR, 1995.

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Flandrin, Patrick. Time-frequency/time scale analysis. San Diego: Academic Press, 1999.

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Tolimieri, Richard. Time-frequency representations. Boston: Birkhauser Boston, 1997.

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Qian, Shie. Joint time-frequency analysis: Methods and applications. Upper Saddle River, N.J: PTR Prentice Hall, 1996.

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Christian, Dunis, and Zhou Bin 1956-, eds. Nonlinear modelling of high frequency financial time series. Chichester [England]: Wiley, 1998.

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Antonia, Papandreou-Suppappola, ed. Applications in time-frequency signal processing. Boca Raton: CRC Press, 2003.

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F, Hlawatsch, and Auger François, eds. Time-frequency analysis: Concepts and tools. London: ISTE, 2008.

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1940-, Cohen Leon, and Loughlin Patrick, eds. Recent developments in time-frequency analysis. Boston: Kluwer Academic Publishers, 1998.

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Privalʹskiĭ, V. E. Time series analysis package: Autoregressive time and frequency domains analysis of scalar and multi-variate time series. Logan, UT: Utah Climate Center, Utah State University, 1993.

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Mueller, Uli. Testing models of low-frequency variability. Cambridge, Mass: National Bureau of Economic Research, 2006.

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Book chapters on the topic "Mixed frequency time series"

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Kundert, Kenneth S., Jacob K. White, and Alberto Sangiovanni-Vincentelli. "Mixed Frequency-Time Method." In Steady-State Methods for Simulating Analog and Microwave Circuits, 157–86. Boston, MA: Springer US, 1990. http://dx.doi.org/10.1007/978-1-4757-2081-5_7.

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Prado, Raquel, Marco A. R. Ferreira, and Mike West. "The frequency domain." In Time Series, 97–130. 2nd ed. Boca Raton: Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781351259422-3.

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Hlawatsch, Franz. "Time-Frequency Filters and Time-Frequency Expansions." In The Kluwer International Series in Engineering and Computer Science, 105–24. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4757-2815-6_5.

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Ramachandra Rao, A., Khaled H. Hamed, and Huey-Long Chen. "Time-Frequency Analysis." In Nonstationarities in Hydrologic and Environmental Time Series, 115–59. Dordrecht: Springer Netherlands, 2003. http://dx.doi.org/10.1007/978-94-010-0117-5_5.

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Riley, Michael D. "Time-frequency filtering." In The Kluwer International Series in Engineering and Computer Science, 53–85. Boston, MA: Springer US, 1989. http://dx.doi.org/10.1007/978-1-4613-1079-2_3.

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Woodward, Wayne A., Bivin P. Sadler, and Stephen D. Robertson. "The Frequency Domain." In Time Series for Data Science, 121–49. New York: Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003089070-4.

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de Gosson, Maurice. "On the Purity and Entropy of Mixed Gaussian States." In Landscapes of Time-Frequency Analysis, 145–58. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-05210-2_5.

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Hirschboeck, Katherine K. "Hydroclimatically-Defined Mixed Distributions in Partial Duration Flood Series." In Hydrologic Frequency Modeling, 199–212. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-009-3953-0_13.

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Lindsey, James K. "Time Series: The Frequency Domain." In The Analysis of Stochastic Processes using GLIM, 133–54. New York, NY: Springer New York, 1992. http://dx.doi.org/10.1007/978-1-4612-2888-2_7.

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Christensen, Ronald. "Frequency Analysis of Time Series." In Springer Texts in Statistics, 152–99. New York, NY: Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4757-3847-6_4.

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Conference papers on the topic "Mixed frequency time series"

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Kennen, Alan, John F. Guravage, Lauren Foster, and John Kornblum. "Investigation of High Frequency Failures on a 0.35μm CMOS IC." In ISTFA 1999. ASM International, 1999. http://dx.doi.org/10.31399/asm.cp.istfa1999p0359.

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Abstract Rapidly changing technology highlights the necessity of developing new failure analysis methodologies. This paper will discuss the combination of two techniques, Design for Test (DFT) and Focused Ion Beam (FIB) analysis, as a means for successfully isolating and identifying a series of high impedance failure sites in a 0.35 μm CMOS design. Although DFT was designed for production testing, the failure mechanism discussed in this paper may not have been isolated without this technique. The device of interest is a mixed signal integrated circuit that provides a digital up-convert function and quadrature modulation. The majority of the circuit functions are digital and as such the majority of the die area is digital. For this analysis, Built In Self Test (BIST) circuitry, an evaluation board for bench testing and FIB techniques were used to successfully identify an unusual failure mechanism. Samples were subjected to Highly Accelerated Stress Test (HAST) as part of the device qualification effort. Post-HAST electrical testing at 200MHz indicated that two units were non-functional. Several different functional blocks on the chip failed electrical testing. One part of the circuitry that failed was the serial interface. The failure analysis team decided to look at the serial interface failure mode first because of the simplicity of the test. After thorough analysis the FA team discovered increasing the data setup time at the serial port input allowed the device to work properly. SEM and FIB techniques were performed which identified a high impedance connection between a metal layer and the underlying via layer. The circuit was modified using a FIB edit, after which all vectors were read back correctly, without the additional set-up time.
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Saville, Jason, Randall Spain, Joan Johnston, and James Lester. "An Analysis of Squad Communication Behaviors during a Field-Training Exercise to Support Tactical Decision Making." In 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022). AHFE International, 2022. http://dx.doi.org/10.54941/ahfe1001498.

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Understanding how teams function in dynamic environments is critical for advancing theories of team development. In this paper, we compared communication behaviors of high and low performing U.S. Army squads that completed a field training event designed to assess tactical decision-making skills and performance under stress. Transcribed audio logs of U.S. Army squad communications were analyzed. A series of 2 (performance group) by 2 (time: Pre-Contact and Post-Contact) mixed-model ANOVAs were conducted to determine whether team communication behaviors changed for squads after coming under duress from hostile contact. Significant main effects for time were found for several communication labels indicating communication patterns differed as task complexity and stressors increased. Significant interaction effects were found between time and performance group for the number of commands given by squad leaders and overall speech frequency. Results highlight the value of examining communications at a granular level as adaptive patterns may otherwise be overlooked.
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Badam, Sriram Karthik, Jieqiong Zhao, Niklas Elmqvist, and David S. Ebert. "TimeFork: Mixed-initiative time-series prediction." In 2014 IEEE Conference on Visual Analytics Science and Technology (VAST). IEEE, 2014. http://dx.doi.org/10.1109/vast.2014.7042501.

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Shen, Yanfeng, Nipon Roy, Junzhen Wang, Zixuan Liu, Danyu Rao, and Wu Xu. "Amplitude and Sweeping Direction Dependent Nonlinear Ultrasonic Resonance Spectroscopy for Fatigue Crack Detection." In ASME 2018 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/imece2018-86221.

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This paper investigates the amplitude and sweeping direction dependent behavior of nonlinear ultrasonic resonance spectroscopy for fatigue crack detection. The Contact Acoustic Nonlinearity (CAN) and the nonlinear resonance phenomena are illuminated via a reduced-order bilinear oscillator model. Unlike conventional linear ultrasonic spectroscopy, which would not change its pattern under different amplitudes of excitation or the frequency sweeping direction, the nonlinear resonance spectroscopy, on the other hand, may be noticeably influenced by both the wave amplitude and the loading history. Both up-tuning and down-tuning sweeping active sensing tests with various levels of excitation amplitudes are performed on a fatigued specimen. Short time Fourier transform is adopted to obtain the time-frequency features of the sensing signal. Corresponding to each excitation frequency, a nonlinear resonance index can be established based on the amplitude ratio between the superhamronic, the subharmonic, the mixed-frequency response components and the fundament frequency. The measured nonlinear resonance spectroscopy for a certain amplitude and frequency sweeping direction can be readily used to establish an instantaneous baseline. The spectroscopy of a different amplitude or frequency sweeping direction can be compared with such an instantaneous baseline and a Damage Index (DI) is obtained by measuring the deviation between the two spectra. Experimental investigations using an aluminum plate with rivet hole nucleated fatigue cracks are performed. A series of nonlinear spectroscopies are analyzed for both the pristine case and the damaged case. The spectral features for both cases are obtained to demonstrate the proposed fatigue crack detection methodology which may find its application for structural health monitoring (SHM). The paper finishes with summary, concluding remarks, and suggestions for future work.
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Kumar, Kuldeep, and Ping Zhang. "Specification of mixed bilinear time series models." In 2015 2nd International Conference on Signal Processing and Integrated Networks (SPIN). IEEE, 2015. http://dx.doi.org/10.1109/spin.2015.7095269.

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Corinaldi, Sharif, and Leon Cohen. "Time-frequency analysis of econometric time series." In SPIE Fourth International Symposium on Fluctuations and Noise, edited by János Kertész, Stefan Bornholdt, and Rosario N. Mantegna. SPIE, 2007. http://dx.doi.org/10.1117/12.726112.

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Ya, Wu, Ke Shiqiu, Yang Shuzi, Xu Shanxiang, Li Weiguo, and Jiang Qiang. "Mixed Time Series Models for Time-Varying Metal Cutting Process." In ASME 1991 Design Technical Conferences. American Society of Mechanical Engineers, 1991. http://dx.doi.org/10.1115/detc1991-0307.

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Abstract The concept of time-varying metal cutting chatter is developed in this paper and the AR and SETAR models based on the segmented time series are introduced to describe the time-variability, which is applied in analyzing the chatter in a type Mx-4 lathe. The emphasis of this work is placed on four aspects: the AR spectrum, the chatter modal damping ratio, the eigenvalues of a time-varying system and the limit cycle for a steady chatter. It is pointed out that, for time-varying chatter, its time interval is quite short compared with ordinary chatter and it will wither away owing to the time-varying parameters of the system. It is also shown that the machine cutting system under steady chatter is still stable and its damping is not equal to zero. The results can well explain the special phenomenon of chatter in Mx-4 lathe and is helpful to the study of time-varying metal cutting chatter.
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Khoo, Wooi Chen, and Seng Huat Ong. "A mixed time series model of binomial counts." In THE 22ND NATIONAL SYMPOSIUM ON MATHEMATICAL SCIENCES (SKSM22): Strengthening Research and Collaboration of Mathematical Sciences in Malaysia. AIP Publishing LLC, 2015. http://dx.doi.org/10.1063/1.4932492.

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Cachucho, Ricardo, Marvin Meeng, Ugo Vespier, Siegfried Nijssen, and Arno Knobbe. "Mining multivariate time series with mixed sampling rates." In UbiComp '14: The 2014 ACM Conference on Ubiquitous Computing. New York, NY, USA: ACM, 2014. http://dx.doi.org/10.1145/2632048.2632061.

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Klabunde, Christian, and Martin Wolter. "Mixed Integer Linear Programming Time-Series Based Redispatch Optimization." In 2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe). IEEE, 2020. http://dx.doi.org/10.1109/isgt-europe47291.2020.9248954.

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Reports on the topic "Mixed frequency time series"

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Diakonova, Marina, Corinna Ghirelli, Luis Molina, and Javier J. Pérez. The economic impact of conflict-related and policy uncertainty shocks: the case of Russia. Madrid: Banco de España, November 2022. http://dx.doi.org/10.53479/23707.

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We show how policy uncertainty and conflict-related shocks impact the dynamics of economic activity (GDP) in Russia. We use alternative indicators of “conflict”, relating to specific aspects of this general concept: geopolitical risk, social unrest, outbreaks of political violence and escalations into internal armed conflict. For policy uncertainty we employ the workhorse economic policy uncertainty (EPU) indicator. We use two distinct but complementary empirical approaches. The first is based on a time series mixed-frequency forecasting model. We show that the indicators provide useful information for forecasting GDP in the short run, even when controlling for a comprehensive set of standard high-frequency macro-financial variables. The second approach, is a SVAR model. We show that negative shocks to the selected indicators lead to economic slowdown, with a persistent drop in GDP growth and a short-lived but large increase in country risk.
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Schorfheide, Frank, and Dongho Song. Real-Time Forecasting with a Mixed-Frequency VAR. Cambridge, MA: National Bureau of Economic Research, December 2013. http://dx.doi.org/10.3386/w19712.

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Schorfheide, Frank, and Dongho Song. Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic. Cambridge, MA: National Bureau of Economic Research, December 2021. http://dx.doi.org/10.3386/w29535.

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McCracken, Michael W., Michael T. Owyang, and Tatevik Sekhposyan. Real-Time Forecasting and Scenario Analysis using a Large Mixed-Frequency Bayesian VAR. Federal Reserve Bank of St. Louis, 2015. http://dx.doi.org/10.20955/wp.2015.030.

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Chiu, Shean-Tsong. Weighted Least Squares Estimators on the Frequency Domain for the Parameters of a Time Series. Fort Belvoir, VA: Defense Technical Information Center, September 1986. http://dx.doi.org/10.21236/ada455201.

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Соловйов, Володимир Миколайович, V. Saptsin, and D. Chabanenko. Markov chains applications to the financial-economic time series predictions. Transport and Telecommunication Institute, 2011. http://dx.doi.org/10.31812/0564/1189.

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In this research the technology of complex Markov chains is applied to predict financial time series. The main distinction of complex or high-order Markov Chains and simple first-order ones is the existing of after-effect or memory. The technology proposes prediction with the hierarchy of time discretization intervals and splicing procedure for the prediction results at the different frequency levels to the single prediction output time series. The hierarchy of time discretizations gives a possibility to use fractal properties of the given time series to make prediction on the different frequencies of the series. The prediction results for world’s stock market indices are presented.
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Kindt, Roeland, Ian K Dawson, Jens-Peter B Lillesø, Alice Muchugi, Fabio Pedercini, and James M Roshetko. The one hundred tree species prioritized for planting in the tropics and subtropics as indicated by database mining. World Agroforestry, 2021. http://dx.doi.org/10.5716/wp21001.pdf.

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A systematic approach to tree planting and management globally is hindered by the limited synthesis of information sources on tree uses and species priorities. To help address this, the authors ‘mined’ information from 23 online global and regional databases to assemble a list of the most frequent tree species deemed useful for planting according to database mentions, with a focus on tropical regions. Using a simple vote count approach for ranking species, we obtained a shortlist of 100 trees mentioned in at least 10 of our data sources (the ‘top-100’ species). A longer list of 830 trees that were mentioned at least five times was also compiled. Our ‘top-100’ list indicated that the family Fabaceae (syn. Leguminosae) was most common. The information associated with our mined data sources indicated that the ‘top-100’ list consisted of a complementary group of species of differing uses. These included the following: for wood (mostly for timber) and fuel production, human nutrition, animal fodder supply, and environmental service provision (varied services). Of these uses, wood was most frequently specified, with fuel and food use also highly important. Many of the ‘top-100’ species were assigned multiple uses. The majority of the ‘top-100’ species had weediness characteristics according to ‘attribute’ invasiveness databases that were also reviewed, thereby demonstrating potential environmental concerns associated with tree planting that need to be balanced against environmental and livelihood benefits. Less than half of the ‘top-100’ species were included in the OECD Scheme for the Certification of Forest Reproductive Material, thus supporting a view that lack of germplasm access is a common concern for trees. A comparison of the ‘top-100’ species with regionally-defined tree inventories indicated their diverse continental origins, as would be anticipated from a global analysis. However, compared to baseline expectations, some geographic regions were better represented than others. Our analysis assists in priority-setting for research and serves as a guide to practical tree planting initiatives. We stress that this ‘top-100’ list does not necessarily represent tree priorities for the future, but provides a starting point for also addressing representation gaps. Indeed, our primary concern going forward is with the latter.
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Phillips, Jake. Understanding the impact of inspection on probation. Sheffield Hallam University, 2021. http://dx.doi.org/10.7190/shu.hkcij.05.2021.

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This research sought to understand the impact of probation inspection on probation policy, practice and practitioners. This important but neglected area of study has significant ramifications because the Her Majesty’s Inspectorate of Probation has considerable power to influence policy through its inspection regime and research activities. The study utilised a mixed methodological approach comprising observations of inspections and interviews with people who work in probation, the Inspectorate and external stakeholders. In total, 77 people were interviewed or took part in focus groups. Probation practitioners, managers and leaders were interviewed in the weeks after an inspection to find out how they experienced the process of inspection. Staff at HMI Probation were interviewed to understand what inspection is for and how it works. External stakeholders representing people from the voluntary sector, politics and other non-departmental bodies were interviewed to find out how they used the work of inspection in their own roles. Finally, leaders within the National Probation Service and Her Majesty’s Prisons and Probation Service were interviewed to see how inspection impacts on policy more broadly. The data were analysed thematically with five key themes being identified. Overall, participants were positive about the way inspection is carried out in the field of probation. The main findings are: 1. Inspection places a burden on practitioners and organisations. Practitioners talked about the anxiety that a looming inspection created and how management teams created additional pressures which were hard to cope with on top of already high workloads. Staff responsible for managing the inspection and with leadership positions talked about the amount of time the process of inspection took up. Importantly, inspection was seen to take people away from their day jobs and meant other priorities were side-lined, even if temporarily. However, the case interviews that practitioners take part in were seen as incredibly valuable exercises which gave staff the opportunity to reflect on their practice and receive positive feedback and validation for their work. 2. Providers said that the findings and conclusions from inspections were often accurate and, to some extent, unsurprising. However, they sometimes find it difficult to implement recommendations due to reports failing to take context into account. Negative reports have a serious impact on staff morale, especially for CRCs and there was concern about the impact of negative findings on a provider’s reputation. 3. External stakeholders value the work of the Inspectorate. The Inspectorate is seen to generate highly valid and meaningful data which stakeholders can use in their own roles. This can include pushing for policy reform or holding government to account from different perspectives. In particular, thematic inspections were seen to be useful here. 4. The regulatory landscape in probation is complex with an array of actors working to hold providers to account. When compared to other forms of regulation such as audit or contract management the Inspectorate was perceived positively due to its methodological approach as well as the way it reflects the values of probation itself. 5. Overall, the inspectorate appears to garner considerable legitimacy from those it inspects. This should, in theory, support the way it can impact on policy and practice. There are some areas for development here though such as more engagement with service users. While recognising that the Inspectorate has made a concerted effort to do this in the last two years participants all felt that more needs to be done to increase that trust between the inspectorate and service users. Overall, the Inspectorate was seen to be independent and 3 impartial although this belief was less prevalent amongst people in CRCs who argued that the Inspectorate has been biased towards supporting its own arguments around reversing the now failed policy of Transforming Rehabilitation. There was some debate amongst participants about how the Inspectorate could, or should, enforce compliance with its recommendations although most people were happy with the primarily relational way of encouraging compliance with sanctions for non-compliance being considered relatively unnecessary. To conclude, the work of the Inspectorate has a significant impact on probation policy, practice and practitioners. The majority of participants were positive about the process of inspection and the Inspectorate more broadly, notwithstanding some of the issues raised in the findings. There are some developments which the Inspectorate could consider to reduce the burden inspection places on providers and practitioners and enhance its impact such as amending the frequency of inspection, improving the feedback given to practitioners and providing more localised feedback, and working to reduce or limit perceptions of bias amongst people in CRCs. The Inspectorate could also do more to capture the impact it has on providers and practitioners – both positive and negative - through existing procedures that are in place such as post-case interview surveys and tracking the implementation of recommendations.
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Hamill, Daniel, and Gabrielle David. Hydrologic analysis of field delineated ordinary high water marks for rivers and streams. Engineer Research and Development Center (U.S.), August 2021. http://dx.doi.org/10.21079/11681/41681.

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Streamflow influences the distribution and organization of high water marks along rivers and streams in a landscape. The federal definition of ordinary high water mark (OHWM) is defined by physical and vegetative field indicators that are used to identify inundation extents of ordinary high water levels without any reference to the relationship between streamflow and regulatory definition. Streamflow is the amount, or volume, of water that moves through a stream per unit time. This study explores regional characteristics and relationships between field-delineated OHWMs and frequency-magnitude streamflow metrics derived from a flood frequency analysis. The elevation of OHWM is related to representative constant-level discharge return periods with national average return periods of 6.9 years using partial duration series and 2.8 years using annual maximum flood frequency approaches. The range in OHWM return periods is 0.5 to 9.08, and 1.05 to 11.01 years for peaks-over-threshold and annual maximum flood frequency methods, respectively. The range of OHWM return periods is consistent with the range found in national studies of return periods related to bankfull streamflow. Hydraulic models produced a statistically significant relationship between OHWM and bank-full, which reinforces the close relationship between the scientific concept and OHWM in most stream systems.
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Chierichetti, Maria, Armin Chierichetti, and Fatemeh Davoudi. Design of an Evaluation Plan for Senate Bill 1046. Mineta Transportation Institute, July 2022. http://dx.doi.org/10.31979/mti.2021.2209.

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In an effort to understand and decrease alcohol-impaired driving as a primary collision factor In California, the research team designed an evaluation plan for California Senate Bill 1046 and its focus on ignition interlock devices as a sentence for Driving Under Influence offense. This plan will evaluate whether Senate Bill 1046 affected the Driving Under the Influence crash frequency and severity, and whether sociodemographic and geographic factors influence its effectiveness. This report lays the foundation for the evaluation that will be conducted in 2024. The research team conducted a meta-analysis of the last 12 years of literature and research on ignition interlock programs inside and outside the United States. Based on the findings of this analysis, the recommended evaluation plan of the law revolves around three research questions that focus on the changes in the frequency/severity of DUI-related crashes in California, the impact of the law on recidivism and on interlock installation rates. To respond to these questions, the research team recommends a list of data that should be collected, such as the number of injuries and deaths resulting from alcohol-related motor vehicle accidents, installation rates of ignition interlocks compared to the prior five-year period, the number of individuals who were required to have an ignition interlock device installed who were convicted of an alcohol-related violation, as well as number of lockouts while an interlock is installed. The research team proposed several statistical approaches for the analysis of this data, such as descriptive statistics, time series analysis, analysis of variance, and logistic regression.
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