Relevant bibliographies by topics / Estimating function

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Estimating function'

Author: Grafiati
Published: 4 June 2021
Last updated: 21 February 2023

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Journal articles on the topic "Estimating function"

1

Liang, Y., A. Thavaneswaran, and B. Abraham. "Joint Estimation Using Quadratic Estimating Function." Journal of Probability and Statistics 2011 (2011): 1–14. http://dx.doi.org/10.1155/2011/372512.

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A class of martingale estimating functions is convenient and plays an important role for inference for nonlinear time series models. However, when the information about the first four conditional moments of the observed process becomes available, the quadratic estimating functions are more informative. In this paper, a general framework for joint estimation of conditional mean and variance parameters in time series models using quadratic estimating functions is developed. Superiority of the approach is demonstrated by comparing the information associated with the optimal quadratic estimating f
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Thavaneswaran, Aerambamoorthy, Saumen Mandal, and Dharini Pathmanathan. "Estimation for Wrapped Zero Inflated Poisson and Wrapped Poisson Distributions." International Journal of Statistics and Probability 5, no. 3 (2016): 1. http://dx.doi.org/10.5539/ijsp.v5n3p1.

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There has been a growing interest in discrete circular models such as wrapped zero inflated Poisson and wrapped Poisson distributions and the trigonometric moments (see Brobbey et al., 2016 and Girija et al., 2014). Also, characteristic functions of stable processes have been used to study the estimation of the model parameters using estimating function approach (see Thavaneswaran et al., 2013). One difficulty in estimating the circular mean and the resultant mean length parameter of wrapped Poisson (WP) or wrapped zero inflated Poisson (WZIP) is that neither the likelihood of WP/WZIP random v
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Miura, Keiji, Masato Okada, and Shun-ichi Amari. "Estimating Spiking Irregularities Under Changing Environments." Neural Computation 18, no. 10 (2006): 2359–86. http://dx.doi.org/10.1162/neco.2006.18.10.2359.

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We considered a gammadistribution of interspike intervals as a statistical model for neuronal spike generation. A gamma distribution is a natural extension of the Poisson process taking the effect of a refractory period into account. The model is specified by two parameters: a time-dependent firing rate and a shape parameter that characterizes spiking irregularities of individual neurons. Because the environment changes over time, observed data are generated from a model with a time-dependent firing rate, which is an unknown function. A statistical model with an unknown function is called a se
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Zhang, Yunyi, Jiazheng Liu, Zexin Pan, and Dimitris N. Politis. "Estimating transformation function." Electronic Journal of Statistics 13, no. 2 (2019): 3095–119. http://dx.doi.org/10.1214/19-ejs1603.

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Mortici, Cristinel. "Estimating gamma function by digamma function." Mathematical and Computer Modelling 52, no. 5-6 (2010): 942–46. http://dx.doi.org/10.1016/j.mcm.2010.05.030.

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Tong, Tiejun, Yanyuan Ma, and Yuedong Wang. "Optimal variance estimation without estimating the mean function." Bernoulli 19, no. 5A (2013): 1839–54. http://dx.doi.org/10.3150/12-bej432.

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Hu, Feifang, and John D. Kalbfleisch. "The estimating function bootstrap." Canadian Journal of Statistics 28, no. 3 (2000): 449–81. http://dx.doi.org/10.2307/3315958.

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Kundu, Piyali, Somesh Kumar, and Kashinath Chatterjee. "Estimating the Reliability Function." Calcutta Statistical Association Bulletin 67, no. 3-4 (2015): 143–61. http://dx.doi.org/10.1177/0008068320150304.

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Roy, R., P. Souchoroukov, and T. Griggs. "Function-based cost estimating." International Journal of Production Research 46, no. 10 (2008): 2621–50. http://dx.doi.org/10.1080/00207540601094440.

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Peszek, Iza, and Andrew L. Rukhin. "Estimating lognormal hazard function." Journal of Statistical Planning and Inference 41, no. 3 (1994): 281–90. http://dx.doi.org/10.1016/0378-3758(94)90024-8.

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Dissertations / Theses on the topic "Estimating function"

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Liang, Longjuan. "A semi-parametric approach to estimating item response functions." Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1180453363.

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Rahikainen, I. (Ilkka). "Direct methodology for estimating the risk neutral probability density function." Master's thesis, University of Oulu, 2014. http://urn.fi/URN:NBN:fi:oulu-201404241289.

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The target of the study is to find out if the direct methodology could provide same information about the parameters of the risk neutral probability density function (RND) than the reference RND methodologies. The direct methodology is based on for defining the parameters of the RND from underlying asset by using futures contracts and only few at-the-money (ATM) and/or close at-the-money (ATM) options on asset. Of course for enabling the analysis of the feasibility of the direct methodology the reference RNDs must be estimated from the option data. Finally the results of estimating the paramet
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Farquharson, Maree Louise. "Estimating the parameters of polynomial phase signals." Thesis, Queensland University of Technology, 2006. https://eprints.qut.edu.au/16312/1/Maree_Farquharson_Thesis.pdf.

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Nonstationary signals are common in many environments such as radar, sonar, bioengineering and power systems. The nonstationary nature of the signals found in these environments means that classicalspectralanalysis techniques are notappropriate for estimating the parameters of these signals. Therefore it is important to develop techniques that can accommodate nonstationary signals. This thesis seeks to achieve this by firstly, modelling each component of the signal as having a polynomial phase and by secondly, developing techniques for estimating the parameters of these components. Several
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Farquharson, Maree Louise. "Estimating the parameters of polynomial phase signals." Queensland University of Technology, 2006. http://eprints.qut.edu.au/16312/.

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Nonstationary signals are common in many environments such as radar, sonar, bioengineering and power systems. The nonstationary nature of the signals found in these environments means that classicalspectralanalysis techniques are notappropriate for estimating the parameters of these signals. Therefore it is important to develop techniques that can accommodate nonstationary signals. This thesis seeks to achieve this by firstly, modelling each component of the signal as having a polynomial phase and by secondly, developing techniques for estimating the parameters of these components. Several app
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SALGADO, MARIA JOSE SEUANEZ. "MONETARY POLICY DURING THE REAL PLAN: ESTIMATING THE CENTRAL BANKS REACTION FUNCTION." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2001. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=14073@1.

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COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR<br>Esta dissertação visa estudar a função de reação do Banco Central do Brasil durante o Plano Real. Argumenta-se que a taxa de juros nominal foi o instrumento mais importante de política monetária, sendo ajustado como resposta a variações na taxa de inflação, hiato do produto, reservas internacionais e ao seu próprio defasado. Estima-se então um modelo linear para a taxa de juros nominal. Em seguida, um Modelo como Limiar (modelo TAR) é usado para explicar uma mudança de regime na taxa de juros. Usando um indicador de crises cambiai
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Alnaji, Lulah A. "Generalized Estimating Equations for Mixed Models." Bowling Green State University / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1530292694012892.

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Glórias, Ludgero Miguel Carraça. "Estimating a knowledge production function and knowledge spillovers : a new two-step estimation procedure of a Spatial Autoregressive Poisson Model." Master's thesis, Instituto Superior de Economia e Gestão, 2020. http://hdl.handle.net/10400.5/20711.

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Mestrado em Econometria Aplicada e Previsão<br>Vários estudos econométricos procuram explicar os determinantes da criação de conhecimento usando como variável dependente o número de patenteamentos numa região. Alguns destes procuram captar os efeitos de Knowledge Spillovers através de modelos lineares que incorporam dependência espacial. No entanto, nenhum estudo foi encontrado que captasse este efeito, tendo em atenção a natureza discreta da variável dependente. Este trabalho pretende preencher essa lacuna propondo um novo estimador de máxima verosimilhança a dois passos para um modelo Poisso
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Cheng, Gang. "The nonparametric least-squares method for estimating monotone functions with interval-censored observations." Diss., University of Iowa, 2012. https://ir.uiowa.edu/etd/2839.

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Monotone function, such as growth function and cumulative distribution function, is often a study of interest in statistical literature. In this dissertation, we propose a nonparametric least-squares method for estimating monotone functions induced from stochastic processes in which the starting time of the process is subject to interval censoring. We apply this method to estimate the mean function of tumor growth with the data from either animal experiments or tumor screening programs to investigate tumor progression. In
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Lim, L. L.-Y. "Statistical methods for the assessment of lung function : Estimating the distribution of ventilation-perfusion ratio from inert gas experiments." Thesis, University of Reading, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.383447.

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Gavin, Victor S. "Evaluation of cost estimating methods for military software application in a COTS environment." Master's thesis, This resource online, 1996. http://scholar.lib.vt.edu/theses/available/etd-02232010-020031/.

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Books on the topic "Estimating function"

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Harrison, R. S. Managing the estimating function. Chartered Institute of Building, 1987.

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Langmaid, John. Estimating: Getting value from function. BSRIA, 2003.

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Drummond, Ian. Estimating with Mk II function point analysis. HMSO, 1992.

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Wildman, Valerie Jean. Estimating effective area surveyed with the cumulative distribution function. Dept. of Statistics, Oregon State University, 1985.

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Software sizing and estimating: Mk II FPA (function point analysis). Wiley, 1991.

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Canright, David. Estimating the spatial extent of attractors of iterated function systems. Naval Postgraduate School, 1993.

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Cuenco, Michael L. Framework for estimating salmon survival as a function of habitat condition. Columbia River Inter-Tribal Fish Commission, 1996.

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Treble, Stephen. Sizing and estimating software in practice: Making MKII function points work. McGraw-Hill, 1995.

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1962-, Douglas Neil, ed. Sizing and estimating software in practice: Making MKII function points work. McGraw-Hill, 1995.

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Attfield, C. L. F. Estimating the UK demand for money function: A test of two approaches. University of Bristol, Department of Economics, 1995.

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Book chapters on the topic "Estimating function"

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Qin, Jing. "Optimal Estimating Function Theory." In Biased Sampling, Over-identified Parameter Problems and Beyond. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4856-2_5.

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Date, Shailesh V. "Estimating Protein Function Using Protein-Protein Relationships." In Gene Function Analysis. Humana Press, 2007. http://dx.doi.org/10.1007/978-1-59745-547-3_7.

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Śliwiński, Przemysław. "Wavelet Network Estimating Regression Function." In Neural Networks and Soft Computing. Physica-Verlag HD, 2003. http://dx.doi.org/10.1007/978-3-7908-1902-1_112.

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Csörgő, Miklós, Lajos Horváth, and Paul Deheuvels. "Estimating the Quantile-Density Function." In Nonparametric Functional Estimation and Related Topics. Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3222-0_16.

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Wang, Guoli, and Michael F. Ochs. "Estimating Gene Function With Least Squares Nonnegative Matrix Factorization." In Gene Function Analysis. Humana Press, 2007. http://dx.doi.org/10.1007/978-1-59745-547-3_3.

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Hu, Feifang. "Bootstrap, Markov Chain and Estimating Function." In Springer Handbook of Engineering Statistics. Springer London, 2006. http://dx.doi.org/10.1007/978-1-84628-288-1_37.

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Pal, Jayanta Kumar, Michael Woodroofe, and Mary Meyer. "Estimating a Polya frequency function$_2$." In Complex Datasets and Inverse Problems. Institute of Mathematical Statistics, 2007. http://dx.doi.org/10.1214/074921707000000184.

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Kang, Min-Jae, Chang-Jin Boo, Ho-Chan Kim, and Jacek M. Zurada. "Estimating Soil Parameters Using the Kernel Function." In Computational Science and Its Applications – ICCSA 2010. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12165-4_9.

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Fischer, Bernd. "Estimating the Spectrum and the Distribution function." In Polynomial Based Iteration Methods for Symmetric Linear Systems. Vieweg+Teubner Verlag, 1996. http://dx.doi.org/10.1007/978-3-663-11108-5_5.

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Ailon, Nir, Bernard Chazelle, Seshadhri Comandur, and Ding Liu. "Estimating the Distance to a Monotone Function." In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-27821-4_21.

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Conference papers on the topic "Estimating function"

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Jindal, Anshul, Mohak Chadha, Shajulin Benedict, and Michael Gerndt. "Estimating the capacities of function-as-a-service functions." In UCC '21: 2021 IEEE/ACM 14th International Conference on Utility and Cloud Computing. ACM, 2021. http://dx.doi.org/10.1145/3492323.3495628.

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Jakobsson, Andreas, Stephen R. Alty, and Jacob Benesty. "Estimating the Two-Dimensional Coherence Function." In 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing. IEEE, 2007. http://dx.doi.org/10.1109/icassp.2007.366849.

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Harrison, Matthew, and Ioannis Kontoyiannis. "On Estimating the Rate-Distortion Function." In 2006 IEEE International Symposium on Information Theory. IEEE, 2006. http://dx.doi.org/10.1109/isit.2006.261847.

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Zeman, Jan. "Estimating of Bellman function via suboptimal strategies." In 2010 IEEE International Conference on Systems, Man and Cybernetics - SMC. IEEE, 2010. http://dx.doi.org/10.1109/icsmc.2010.5641952.

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Kang, Byeongdo, and Jongseok Lee. "Estimating Procedure for Function Point Analysis in Korea." In 2018 19th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD). IEEE, 2018. http://dx.doi.org/10.1109/snpd.2018.8441088.

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Colson, T., B. Boterhoven, D. Castillo, and M. Keep. "Estimating the Coulomb Failure Function Using Seismic Velocities." In Fourth International Conference on Fault and Top Seals. EAGE Publications BV, 2015. http://dx.doi.org/10.3997/2214-4609.201414069.

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Sikka, Geeta, Arvinder Kaur, and Moin Uddin. "Estimating function points: Using machine learning and regression models." In 2010 2nd International Conference on Education Technology and Computer (ICETC). IEEE, 2010. http://dx.doi.org/10.1109/icetc.2010.5529600.

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Shen, Jin, Gang Zheng, Mengchao Li, and Guoqiang Sun. "Improving methods of estimating autocorrelation function in PCS technique." In Photonics Asia 2002, edited by Zhicheng Weng, Jose M. Sasian, and Yongtian Wang. SPIE, 2002. http://dx.doi.org/10.1117/12.471673.

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Chelli, Ali, and Matthias Patzold. "An improved method for estimating the frequency correlation function." In 2012 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2012. http://dx.doi.org/10.1109/wcnc.2012.6213930.

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Penmetsa, Ravi, and Ramana Grandhi. "Estimating Membership Function of Implicit Response Using Surrogate Models." In 43rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference. American Institute of Aeronautics and Astronautics, 2002. http://dx.doi.org/10.2514/6.2002-1234.

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Reports on the topic "Estimating function"

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Hall, Peter, and R. J. Carroll. Variance Function Estimation in Regression: The Effect of Estimating the Mean. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada198228.

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Al Gahtani, Goblan, Carlo Andrea Bollino, Simona Bigerna, and Axel Pierru. Estimating the Household Consumption Function in Saudi Arabia. King Abdullah Petroleum Studies and Research Center, 2019. http://dx.doi.org/10.30573/ks--2019-dp50.

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Canright, D. Estimating the Spatial Extent of Attractors of Iterated Function System. Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/ada265856.

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Ito, Takatoshi, and Tomoyoshi Yabu. Japanese Foreign Exchange Interventions, 1971-2018: Estimating a Reaction Function Using the Best Proxy. National Bureau of Economic Research, 2020. http://dx.doi.org/10.3386/w26644.

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Attanasio, Orazio, Sarah Cattan, Emla Fitzsimons, Costas Meghir, and Marta Rubio-Codina. Estimating the Production Function for Human Capital: Results from a Randomized Control Trial in Colombia. National Bureau of Economic Research, 2015. http://dx.doi.org/10.3386/w20965.

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Attanasio, Orazio, Marta Rubio Codina, Sarah Cattan, Emla Fitzsimons, and Costas Meghir. Estimating the production function for human capital: results from a randomized controlled trial in Colombia. IFS, 2015. http://dx.doi.org/10.1920/wp.ifs.2015.1506.

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Rubio Codina, Marta, Orazio Attanasio, Sarah Cattan, Emla Fitzsimons, and Costas Meghir. Estimating the production function for human capital: results from a randomized controlled trial in Colombia. The IFS, 2017. http://dx.doi.org/10.1920/wp.ifs.2017.1706.

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Rubio Codina, Marta, Costas Meghir, Emla Fitzsimons, Sarah Cattan, and Orazio Attanasio. Estimating the production function for human capital: results from a randomized controlled trial in Colombia. The IFS, 2020. http://dx.doi.org/10.1920/wp.ifs.2020.320.

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Read, Matthew. Estimating the Effects of Monetary Policy in Australia Using Sign-restricted Structural Vector Autoregressions. Reserve Bank of Australia, 2023. http://dx.doi.org/10.47688/rdp2022-09.

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Existing estimates of the macroeconomic effects of Australian monetary policy tend to be based on strong, potentially contentious, assumptions. I estimate these effects under weaker assumptions. Specifically, I estimate a structural vector autoregression identified using a variety of sign restrictions, including restrictions on impulse responses to a monetary policy shock, the monetary policy reaction function, and the relationship between the monetary policy shock and a proxy for this shock. I use an approach to Bayesian inference that accounts for the problem of posterior sensitivity to the
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Kott, Phillip S. The Role of Weights in Regression Modeling and Imputation. RTI Press, 2022. http://dx.doi.org/10.3768/rtipress.2022.mr.0047.2203.

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When fitting observations from a complex survey, the standard regression model assumes that the expected value of the difference between the dependent variable and its model-based prediction is zero, regardless of the values of the explanatory variables. A rarely failing extended regression model assumes only that the model error is uncorrelated with the model’s explanatory variables. When the standard model holds, it is possible to create alternative analysis weights that retain the consistency of the model-parameter estimates while increasing their efficiency by scaling the inverse-probabili
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