Relevant bibliographies by topics / Partial least squares analysis

Academic literature on the topic 'Partial least squares analysis'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Contents

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Partial least squares analysis.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Partial least squares analysis"

1

Liland, Kristian Hovde, and Ulf Geir Indahl. "Powered partial least squares discriminant analysis." Journal of Chemometrics 23, no. 1 (January 2009): 7–18. http://dx.doi.org/10.1002/cem.1186.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Ketterlinus, Robert D., Fred L. Bookstein, Paul D. Sampson, and Michael E. Lamb. "Partial least squares analysis in developmental psychopathology." Development and Psychopathology 1, no. 4 (October 1989): 351–71. http://dx.doi.org/10.1017/s0954579400000523.

Full text
Abstract:
AbstractDespite extensive theoretical and empirical advances in the last two decades, little attention has been paid to the development of statistical techniques suited for the analysis of data gathered in studies of developmental psychopathology. As in most other studies of developmental processes, research in this area often involves complex constructs, such as intelligence and antisocial behavior, measured indirectly using multiple observed indicators. Relations between pairs of such constructs are sometimes reported in terms of latent variables (LVs): linear combinations of the indicators of each construct. We introduce the assumptions and procedures associated with one method for exploring these relations: partial least squares (PLS) analysis, which maximizes covariances between predictor and outcome LVs; its coefficients are correlations between observed variables and LVs, and its LVs are sums of observable variables weighted by these correlations. In the least squares logic of PLS, familiar notions about simple regressions and principal component analyses may be reinterpreted as rules for including or excluding particular blocks in a model and for “splitting” blocks into multiple dimensions. Guidelines for conducting PLS analyses and interpreting their results are provided using data from the Goteborg Daycare Study and the Seattle Longitudinal Prospective Study on Alcohol and Pregnancy. The major advantages of PLS analysis are that it (1) concisely summarizes the intercorrelations among a large number of variables regardless of sample size, (2) yields coefficients that are readily interpretable, and (3) provides straightforward decision rules about modeling. The advantages make PLS a highly desirable technique for use in longitudinal research on developmental psychopathology. The primer is written primarily for the nonstatistician, although formal mathematical details are provided in Appendix 1.
APA, Harvard, Vancouver, ISO, and other styles
3

Stoica, Petre, and Torsten Söderström. "Partial Least Squares: A First‐order Analysis." Scandinavian Journal of Statistics 25, no. 1 (March 1998): 17–24. http://dx.doi.org/10.1111/1467-9469.00085.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Kumar, S., U. Kruger, E. B. Martin, and A. J. Morris. "Analysis of Nonlinear Partial Least Squares Algorithms." IFAC Proceedings Volumes 37, no. 9 (July 2004): 739–44. http://dx.doi.org/10.1016/s1474-6670(17)31898-0.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Qing Wang, Feng Chen, Wenli Xu, and Ming-Hsuan Yang. "Object Tracking via Partial Least Squares Analysis." IEEE Transactions on Image Processing 21, no. 10 (October 2012): 4454–65. http://dx.doi.org/10.1109/tip.2012.2205700.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Jin, Xi, Xing Zhang, Kaifeng Rao, Liang Tang, and Qiwei Xie. "Semi-supervised partial least squares." International Journal of Wavelets, Multiresolution and Information Processing 18, no. 03 (January 13, 2020): 2050014. http://dx.doi.org/10.1142/s0219691320500149.

Full text
Abstract:
Traditional supervised dimensionality reduction methods can establish a better model often under the premise of a large number of samples. However, in real-world applications where labeled data are scarce, traditional methods tend to perform poorly because of overfitting. In such cases, unlabeled samples could be useful in improving the performance. In this paper, we propose a semi-supervised dimensionality reduction method by using partial least squares (PLS) which we call semi-supervised partial least squares (S2PLS). To combine the labeled and unlabeled samples into a S2PLS model, we first apply the PLS algorithm to unsupervised dimensionality reduction. Then, the final S2PLS model is established by ensembling the supervised PLS model and the unsupervised PLS model which using the basic idea of principal model analysis (PMA) method. Compared with unsupervised or supervised dimensionality reduction algorithms, S2PLS not only can improve the prediction accuracy of the samples but also enhance the generalization ability of the model. Meanwhile, it can obtain better results even there are only a few or no labeled samples. Experimental results on five UCI data sets also confirmed the above properties of S2PLS algorithm.
APA, Harvard, Vancouver, ISO, and other styles
7

Simonin, Dimitri, and Bernard Morard. "Introducing an Optimal (and a Simpler) Approach to Partial Least Squares Analyses." International Journal of Trade, Economics and Finance 8, no. 1 (February 2017): 1–11. http://dx.doi.org/10.18178/ijtef.2017.8.1.531.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Arioli, Mario, Marc Baboulin, and Serge Gratton. "A Partial Condition Number for Linear Least Squares Problems." SIAM Journal on Matrix Analysis and Applications 29, no. 2 (January 2007): 413–33. http://dx.doi.org/10.1137/050643088.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Alsberg, Bjørn K., Douglas B. Kell, and Royston Goodacre. "Variable Selection in Discriminant Partial Least-Squares Analysis." Analytical Chemistry 70, no. 19 (October 1998): 4126–33. http://dx.doi.org/10.1021/ac980506o.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Nitzl, Christian, Jose L. Roldan, and Gabriel Cepeda. "Mediation analysis in partial least squares path modeling." Industrial Management & Data Systems 116, no. 9 (October 17, 2016): 1849–64. http://dx.doi.org/10.1108/imds-07-2015-0302.

Full text
Abstract:
Purpose Indirect or mediated effects constitute a type of relationship between constructs that often occurs in partial least squares (PLS) path modeling. Over the past few years, the methods for testing mediation have become more sophisticated. However, many researchers continue to use outdated methods to test mediating effects in PLS, which can lead to erroneous results. One reason for the use of outdated methods or even the lack of their use altogether is that no systematic tutorials on PLS exist that draw on the newest statistical findings. The paper aims to discuss these issues. Design/methodology/approach This study illustrates the state-of-the-art use of mediation analysis in the context of PLS-structural equation modeling (SEM). Findings This study facilitates the adoption of modern procedures in PLS-SEM by challenging the conventional approach to mediation analysis and providing more accurate alternatives. In addition, the authors propose a decision tree and classification of mediation effects. Originality/value The recommended approach offers a wide range of testing options (e.g. multiple mediators) that go beyond simple mediation analysis alternatives, helping researchers discuss their studies in a more accurate way.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Partial least squares analysis"

1

Moller, Jurgen Johann. "The implementation of noise addition partial least squares." Thesis, Stellenbosch : University of Stellenbosch, 2009. http://hdl.handle.net/10019.1/3362.

Full text
Abstract:
Thesis (MComm (Statistics and Actuarial Science))--University of Stellenbosch, 2009.
When determining the chemical composition of a specimen, traditional laboratory techniques are often both expensive and time consuming. It is therefore preferable to employ more cost effective spectroscopic techniques such as near infrared (NIR). Traditionally, the calibration problem has been solved by means of multiple linear regression to specify the model between X and Y. Traditional regression techniques, however, quickly fail when using spectroscopic data, as the number of wavelengths can easily be several hundred, often exceeding the number of chemical samples. This scenario, together with the high level of collinearity between wavelengths, will necessarily lead to singularity problems when calculating the regression coefficients. Ways of dealing with the collinearity problem include principal component regression (PCR), ridge regression (RR) and PLS regression. Both PCR and RR require a significant amount of computation when the number of variables is large. PLS overcomes the collinearity problem in a similar way as PCR, by modelling both the chemical and spectral data as functions of common latent variables. The quality of the employed reference method greatly impacts the coefficients of the regression model and therefore, the quality of its predictions. With both X and Y subject to random error, the quality the predictions of Y will be reduced with an increase in the level of noise. Previously conducted research focussed mainly on the effects of noise in X. This paper focuses on a method proposed by Dardenne and Fernández Pierna, called Noise Addition Partial Least Squares (NAPLS) that attempts to deal with the problem of poor reference values. Some aspects of the theory behind PCR, PLS and model selection is discussed. This is then followed by a discussion of the NAPLS algorithm. Both PLS and NAPLS are implemented on various datasets that arise in practice, in order to determine cases where NAPLS will be beneficial over conventional PLS. For each dataset, specific attention is given to the analysis of outliers, influential values and the linearity between X and Y, using graphical techniques. Lastly, the performance of the NAPLS algorithm is evaluated for various
APA, Harvard, Vancouver, ISO, and other styles
2

Krämer, Nicole. "Analysis of high dimensional data with partial least squares and boosting." [S.l.] : [s.n.], 2006. http://opus.kobv.de/tuberlin/volltexte/2007/1484.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Li, Siqing. "Kernel-based least-squares approximations: theories and applications." HKBU Institutional Repository, 2018. https://repository.hkbu.edu.hk/etd_oa/539.

Full text
Abstract:
Kernel-based meshless methods for approximating functions and solutions of partial differential equations have many applications in engineering fields. As only scattered data are used, meshless methods using radial basis functions can be extended to complicated geometry and high-dimensional problems. In this thesis, kernel-based least-squares methods will be used to solve several direct and inverse problems. In chapter 2, we consider discrete least-squares methods using radial basis functions. A general l^2-Tikhonov regularization with W_2^m-penalty is considered. We provide error estimates that are comparable to kernel-based interpolation in cases in which the function being approximated is within and is outside of the native space of the kernel. These results are extended to the case of noisy data. Numerical demonstrations are provided to verify the theoretical results. In chapter 3, we apply kernel-based collocation methods to elliptic problems with mixed boundary conditions. We propose some weighted least-squares formulations with different weights for the Dirichlet and Neumann boundary collocation terms. Besides fill distance of discrete sets, our weights also depend on three other factors: proportion of the measures of the Dirichlet and Neumann boundaries, dimensionless volume ratios of the boundary and domain, and kernel smoothness. We determine the dependencies of these terms in weights by different numerical tests. Our least-squares formulations can be proved to be convergent at the H^2 (Ω) norm. Numerical experiments in two and three dimensions show that we can obtain desired convergent results under different boundary conditions and different domain shapes. In chapter 4, we use a kernel-based least-squares method to solve ill-posed Cauchy problems for elliptic partial differential equations. We construct stable methods for these inverse problems. Numerical approximations to solutions of elliptic Cauchy problems are formulated as solutions of nonlinear least-squares problems with quadratic inequality constraints. A convergence analysis with respect to noise levels and fill distances of data points is provided, from which a Tikhonov regularization strategy is obtained. A nonlinear algorithm is proposed to obtain stable solutions of the resulting nonlinear problems. Numerical experiments are provided to verify our convergence results. In the final chapter, we apply meshless methods to the Gierer-Meinhardt activator-inhibitor model. Pattern transitions in irregular domains of the Gierer-Meinhardt model are shown. We propose various parameter settings for different patterns appearing in nature and test these settings on some irregular domains. To further simulate patterns in reality, we construct different kinds of domains and apply proposed parameter settings on different patches of domains found in nature.
APA, Harvard, Vancouver, ISO, and other styles
4

Zhou, Yue. "Analysis of Additive Risk Model with High Dimensional Covariates Using Partial Least Squares." Digital Archive @ GSU, 2006. http://digitalarchive.gsu.edu/math_theses/6.

Full text
Abstract:
In this thesis, we consider the problem of constructing an additive risk model based on the right censored survival data to predict the survival times of the cancer patients, especially when the dimension of the covariates is much larger than the sample size. For microarray Gene Expression data, the number of gene expression levels is far greater than the number of samples. Such ¡°small n, large p¡± problems have attracted researchers to investigate the association between cancer patient survival times and gene expression profiles for recent few years. We apply Partial Least Squares to reduce the dimension of the covariates and get the corresponding latent variables (components), and these components are used as new regressors to fit the extensional additive risk model. Also we employ the time dependent AUC curve (area under the Receiver Operating Characteristic (ROC) curve) to assess how well the model predicts the survival time. Finally, this approach is illustrated by re-analysis of the well known AML data set and breast cancer data set. The results show that the model fits both of the data sets very well.
APA, Harvard, Vancouver, ISO, and other styles
5

Skoglund, Ingegerd. "Algorithms for a Partially Regularized Least Squares Problem." Licentiate thesis, Linköping : Linköpings universitet, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-8784.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Yue, Weiping Biotechnology &amp Biomolecular Sciences Faculty of Science UNSW. "Predicting the citation impact of clinical neurology journals using structural equation modeling with partial least squares." Awarded by:University of New South Wales. School of Biotechnology and Biomolecular Sciences, 2004. http://handle.unsw.edu.au/1959.4/20821.

Full text
Abstract:
The ongoing debate on the evaluative role of citation analysis and the theory of citation recognizes that the citation process is complex and that citation counts are affected by certain extra-scientific or external factors. To date, little effort has been made to explore the effects of various external factors; this thesis addresses this lack. In the context of the various perspectives on citations and citation analysis, this study uses journals as the unit of analysis and investigates what, how, and to what extent extra-scientific factors influence the citation impact of journals. An integrated conceptual model of Journal Citation Impact that takes into account current theoretical positions and prior empirical research findings is developed. It addresses the interrelationships between Journal Citation Impact and a range of external factors (Journal Properties, Journal Visibility, Journal Accessibility, Journal Internationality, Journal Selectivity, Journal Promptness, Journal Editorial Prestige, and Perceived Journal Quality). The proposed conceptual model is novel in that it: (1) incorporates nearly all possible external factors that affect Journal Citation Impact; (2) addresses the complex interrelationships between a number of external factors and Journal Citation Impact in one model; (3) regards both Journal Citation Impact and its external factors as theoretical constructs; and (4) identifies the observed variables of the external factors and Journal Citation Impact. However, because of the difficulties in operationalizing all the theoretical constructs, this conceptual model is simplified to an operational model for empirical testing. The operational model includes the construct Journal Citation Impact and four of its external factors, Journal Properties, Journal Accessibility, Journal Internationality, and Perceived Journal Quality. Structural Equation Modeling (SEM) with Partial Least Squares (PLS) is used to test the operational model with empirical data from 41 research journals in clinical neurology. Data are collected from bibliographic database searching, web searching, printed journals, and from a web-based survey that was conducted to obtain information on perceptions of journal quality. Empirical results of the operational model show that Journal Accessibility, Journal Internationality, and Perceived Journal Quality have large, medium, and small effects respectively on Journal Citation Impact, thus indicating that certain extra-scientific factors can influence Journal Citation Impact significantly. The findings suggest that great care should be taken in interpreting and evaluating the results obtained from citation analysis. In terms of Journal Citation Impact, this research also suggests that various journal citation indicators should be ii used to reflect different aspects of citation impact. By exploring the phenomenological domain in the citing process, this exploratory study not only provides a better understanding of citation analysis, it also contributes to the development of the theory of citation. From the methodological perspective, introducing SEM with PLS to Informetrics and Scientometrics also contributes to the knowledge base of these fields. Pragmatically, the research findings will enhance the judgment of researchers and practitioners such as editors, publishers, librarians and other information specialists in assessing journal performance. Finally, the worldwide survey findings on peer assessment of journal outlets in clinical neurology will be useful for researchers, academics or clinicians in this field.
APA, Harvard, Vancouver, ISO, and other styles
7

Patten, Kyle. "An analysis of the modeling used to determine customer satisfaction." Thesis, Kansas State University, 2014. http://hdl.handle.net/2097/35765.

Full text
Abstract:
Master of Agribusiness
Department of Agricultural Economics
Kevin Dhuyvetter
Many companies use surveys to establish customer satisfaction metrics. This OEM has been using surveys to analyze customer satisfaction with their products, services, and distribution channel for several decades. Satisfaction metrics are established for the brand, product, and channel partners. The product metric is derived from a question on the survey asking customers how satisfied they are with the product. There are subsequent questions thereafter inquiring about satisfaction with specific functional areas of the product. It is common practice to use Partial Least Squares (PLS) regression analysis to evaluate what impacts the functional area questions have on the overall satisfaction question. The model results are used to understand what areas of the machine should be focused on to improve customers’ experiences with the machine. These results are compared to other data sources such as warranty, field reports, customer focus groups, etc. The results from these models are sometimes questioned based on what common intuition would suggest. Typically the top three drivers to the product metric are understandable, but there are often one or two key areas that do not make logical sense. The objective of this thesis was to understand whether PLS modeling is appropriate given the nature of customer survey data. Models were estimated using existing survey data on a specific model in the tractor product line. PLS models assume data are linear with no bounds. This in itself likely makes this type of model inappropriate for analyzing customer survey data. Responses are bounded on an 11 point scale from 0-10, however, the PLS model being non-bounded assumes there can be a score under 0 or over 10. The model also assumes a linear slope that would indicate each covariate answer 0-10 has the same level of effect on the response variable. This research has found that each covariate answer is in fact non-linear. For example, a customer answering a 2 to quality of manufacturing workmanship has a different impact on the overall satisfaction score than a customer who answers 8. Finally, this research discovered that the PLS models produce negative coefficients of significant value that are not reported to the enterprise. Binary and ordered logistic (logit) models were estimated as an alternative to PLS. Logistic models are non-linear and are commonly used to evaluate bounded data. Response data were separated into two groups based on Net Promoter Score (NPS) Methodology (Reicheld 2006). Using the NPS methodology, 0-6 scores are considered detractors, 7-8 scores are considered passives, and 9-10 scores are considered promoters. The logistic models demonstrate that the top two drivers to customer satisfaction scores are still quality of manufacturing workmanship and reliability/operational availability (similar to results of the PLS model). The unresolved problems question on the survey was included in the models and demonstrated that the predicted probability of a customer being a promoter is much higher in both binary and ordered logit models if no unresolved problems exist. Finally, the model found engine oil consumption remained negative and is statistically significant suggesting that even with the alternative modeling approach there still may be data issues related to the survey. It is recommended that the OEM implement logistic modeling for analyzing customer survey data. It is also recommended that a new survey design be constructed to eliminate issues with correlated data that can lead to spurious and unexplainable results.
APA, Harvard, Vancouver, ISO, and other styles
8

Nguyen, Nga. "Multivariate analysis and GIS in generating vulnerability map of acid sulfate soils." Thesis, KTH, Mark- och vattenteknik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-170472.

Full text
Abstract:
The study employed multi-variate methods to generate vulnerability maps for acid sulfate soils (AS) in the Norrbotten county of Sweden. In this study, the relationships between the reclassified datasets and each biogeochemical element was carefully evaluated with ANOVA Kruskal Wallis and PLS analysis. The sta-tistical results of ANOVA Kruskall-Wallis provided us a useful knowledge of the relationships of the preliminary vulnerability ranks in the classified datasets ver-sus the amount of each biogeochemical element. Then, the statistical knowledge and expert knowledge were used to generate the final vulnerability ranks of AS soils in the classified datasets which were the input independent variables in PLS analyses. The results of Kruskal-Wallis one way ANOVA and PLS analyses showed a strong correlation of the higher levels total Cu2+, Ni2+ and S to the higher vulnerability ranks in the classified datasets. Hence, total Cu2+, Ni2+ and S were chosen as the dependent variables for further PLS analyses. In particular, the Variable Importance in the Projection (VIP) value of each classified dataset was standardized to generate its weight. Vulnerability map of AS soil was a result of a lineal combination of the standardized values in the classified dataset and its weight. Seven weight sets were formed from either uni-variate or multi-variate PLS analyses. Accuracy tests were done by testing the classification of measured pH values of 74 soil profiles with different vulnerability maps and evaluating the areas that were not the AS soil within the groups of medium to high AS soil probability in the land-cover and soil-type datasets. In comparison to the other weight sets, the weight set of multi-variate PLS analysis of the matrix of total Ni2+& S or total Cu2+& S had the robust predictive performance. Sensitivity anal-ysis was done in the weight set of total Ni2+& S, and the results of sensitivity analyses showed that the availability of ditches, and the change in the terrain sur-faces, the altitude level, and the slope had a high influence to the vulnerability map of AS soils. The study showed that using multivariate analysis was a very good approach methodology for predicting the probability of acid sulfate soil.
APA, Harvard, Vancouver, ISO, and other styles
9

Sinioja, Tim. ""Source characterization of soils contaminated with Polycyclic Aromatic Compounds (PACs) by use of Partial Least Squares Discriminant Analysis (PLS-DA)"." Thesis, Örebro universitet, Institutionen för naturvetenskap och teknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-64627.

Full text
Abstract:
Polycyclic aromatic compounds (PACs) are organic compounds that include several sub-groups of toxic, persistent and carcinogenic environmental pollutants consisting of two or more non-substituted or substituted aromatic rings. Due to the complexity of PAC-mixtures found in the environment it can be challenging and time-consuming to track the sources of contamination. In the present study, multivariate data analysis (MVDA) models, such as principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were applied to track sources of PACs at contaminated sites. Based on the chemical profile of 78 PACs obtained in GC-MS analysis of soils, 26 observations were classified according to their petrogenic, pyrogenic or urban background soil origin. Two soil samples of unknown origin collected at a contaminated site in Mjölby, Sweden, were successfully fitted to the validated PLS-DA model and their origins were determined as petrogenic. The study shows that validated PLS-DA models can be applied to predict the petrogenic, pyrogenic and urban background soil origins of samples collected at PAC contaminated sites, thus to track the sources of contamination. It is also concluded that 16 U.S. Environmental Protection Agency’s (EPA) priority polycyclic aromatic hydrocarbons (PAHs) are not sufficient to predict the origin of contamination with PCA or PLS-DA.
APA, Harvard, Vancouver, ISO, and other styles
10

Hassling, Andreas, and Simon Flink. "SYSTEM IDENTIFICATION OF A WASTE-FIRED CFB BOILER : Using Principal Component Analysis (PCA) and Partial Least Squares Regression modeling (PLS-R)." Thesis, Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-34979.

Full text
Abstract:
Heat and electricity production along with waste management are two modern day challenges for society. One of the possible solution to both of them is the incineration of household waste to produce heat and electricity. Incineration is a waste-to-energy treatment process, which can reduce the need for landfills and save the use of more valuable fuels, thereby conserving natural resources. This report/paper investigates the performance and emissions of a municipal solid waste (MSW) fueled industrial boiler by performing a system identification analysis using Principle Component Analysis (PCA) and Partial Least Squares Regression (PLS-R) modeling. The boiler is located in Västerås, Sweden and has a maximum capacity of 167MW. It produces heat and electricity for the city of Västerås and is operated by Mälarenergi AB. A dataset containing 148 different boilers variables, measured with a one hour interval over 2 years, was used for the system identification analysis. The dataset was visually inspected to remove obvious outliers before beginning the analysis using a multivariate data analysis software called The Unscrambler X (Version 10.3, CAMO Software, Norway). Correlations found using PCA was taken in account during the PLSR modelling where models were created for one response each. Some variables had an unexpected impact on the models while others were fully logical regarding combustion theory. Results found during the system analysis process are regarded as reliable. Any errors may be due to outlier data points and model inadequacies.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Books on the topic "Partial least squares analysis"

1

Lohmöller, Jan-Bernd. Latent variable path modeling with partial least squares. Heidelberg: Physica-Verlag, 1989.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
2

Banks, H. Thomas. Analytic semigroups: Applications to inverse problems for flexible structures. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1990.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
3

Esposito Vinzi, Vincenzo, Wynne W. Chin, Jörg Henseler, and Huiwen Wang, eds. Handbook of Partial Least Squares. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-540-32827-8.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Latan, Hengky, and Richard Noonan, eds. Partial Least Squares Path Modeling. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64069-3.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Avkiran, Necmi K., and Christian M. Ringle, eds. Partial Least Squares Structural Equation Modeling. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-71691-6.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Bochev, Pavel B. Least-squares finite element methods. New York: Springer, 2009.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
7

Linear least squares computations. New York: Marcel Dekker, 1988.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
8

1944-, Hilbe Joseph M., ed. Quasi-least squares regression. Boca Raton: CRC Press, Taylor & Francis Group, 2014.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
9

D, Gunzburger Max, ed. Least-squares finite element methods. New York: Springer, 2009.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
10

Bochev, Pavel B. Least-squares finite element methods. New York: Springer, 2009.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Book chapters on the topic "Partial least squares analysis"

1

Westland, J. Christopher. "Partial Least Squares Path Analysis." In Structural Equation Models, 23–46. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16507-3_3.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Westland, J. Christopher. "Partial Least Squares Path Analysis." In Structural Equation Models, 17–38. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12508-0_2.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Wang, Huiwen, Jie Meng, and Michel Tenenhaus. "Regression Modelling Analysis on Compositional Data." In Handbook of Partial Least Squares, 381–406. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-32827-8_18.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Latan, Hengky, Charbel Jose Chiappetta Jabbour, and Ana Beatriz Lopes de Sousa Jabbour. "Ethical Awareness, Ethical Judgment, and Whistleblowing: A Moderated Mediation Analysis." In Partial Least Squares Path Modeling, 311–37. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64069-3_15.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Kock, Ned. "Going Beyond Composites: Conducting a Factor-Based PLS-SEM Analysis." In Partial Least Squares Path Modeling, 41–53. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64069-3_3.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Ringle, Christian M., Sven Wende, and Alexander Will. "Finite Mixture Partial Least Squares Analysis: Methodology and Numerical Examples." In Handbook of Partial Least Squares, 195–218. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-32827-8_9.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Matthews, Lucy. "Applying Multigroup Analysis in PLS-SEM: A Step-by-Step Process." In Partial Least Squares Path Modeling, 219–43. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64069-3_10.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Tenenhaus, Michel, and Mohamed Hanafi. "A Bridge Between PLS Path Modeling and Multi-Block Data Analysis." In Handbook of Partial Least Squares, 99–123. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-32827-8_5.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Hulland, John, Michael J. Ryan, and Robert K. Rayner. "Modeling Customer Satisfaction: A Comparative Performance Evaluation of Covariance Structure Analysis Versus Partial Least Squares." In Handbook of Partial Least Squares, 307–25. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-32827-8_15.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Krishnan, Anjali, Nikolaus Kriegeskorte, and Hervé Abdi. "Distance-Based Partial Least Squares Analysis." In Springer Proceedings in Mathematics & Statistics, 131–45. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8283-3_8.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Partial least squares analysis"

1

Mou, Yi, Xinge You, Xiubao Jiang, Duanquan Xu, and Shujian Yu. "Global sparse partial least squares." In 2014 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC). IEEE, 2014. http://dx.doi.org/10.1109/spac.2014.6982713.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Schwartz, William Robson, Aniruddha Kembhavi, David Harwood, and Larry S. Davis. "Human detection using partial least squares analysis." In 2009 IEEE 12th International Conference on Computer Vision (ICCV). IEEE, 2009. http://dx.doi.org/10.1109/iccv.2009.5459205.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Liu, Huawen, Zongjie Ma, Jianmin Zhao, and Zhonglong Zheng. "Penalized partial least squares for multi-label data." In 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). IEEE, 2014. http://dx.doi.org/10.1109/asonam.2014.6921635.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Asadifard, Roya. "Public policy analysis in Iran: the partial least square test." In 2nd International Symposium on Partial Least Squares Path Modeling - The Conference for PLS Users. University of Twente, 2015. http://dx.doi.org/10.3990/2.321.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Li, Weiguo, Hanjie Zhang, Xiaoping Du, Kun Qian, and Cuiying Li. "Data analysis of roadway attributes through Partial Least Squares regression." In 2010 2nd IEEE International Conference on Information and Financial Engineering (ICIFE). IEEE, 2010. http://dx.doi.org/10.1109/icife.2010.5609399.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Fischer, Mika, Hazim Kemal Ekenel, and Rainer Stiefelhagen. "Analysis of partial least squares for pose-invariant face recognition." In 2012 IEEE Fifth International Conference On Biometrics: Theory, Applications And Systems (BTAS). IEEE, 2012. http://dx.doi.org/10.1109/btas.2012.6374597.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Wang, Ping, and Hong Zhang. "Multi-kernel Partial Least Squares for Multi-Modal Data Analysis." In 2016 7th International Conference on Education, Management, Computer and Medicine (EMCM 2016). Paris, France: Atlantis Press, 2017. http://dx.doi.org/10.2991/emcm-16.2017.177.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Zhang, Feng, xiaojun tang, angxin tong, bin wang, leilei xi, and wei qiu. "Using Least Squares Support Vector Machine and Polynomial Partial Least Squares Method Quantitative Analysis of Gases in Mines." In 2019 IEEE 5th Intl Conference on Big Data Security on Cloud (BigDataSecurity), IEEE Intl Conference on High Performance and Smart Computing, (HPSC) and IEEE Intl Conference on Intelligent Data and Security (IDS). IEEE, 2019. http://dx.doi.org/10.1109/bigdatasecurity-hpsc-ids.2019.00034.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Zuhal, Lavi Rizki, Ghifari A. Faza, Pramudita S. Palar, and Rhea P. Liem. "Fast and Adaptive Reliability Analysis via Kriging and Partial Least Squares." In AIAA Scitech 2021 Forum. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2021. http://dx.doi.org/10.2514/6.2021-0675.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Zhu, Jun, Weijia Zou, Xiaokang Yang, Rui Zhang, Quan Zhou, and Wenju Zhang. "Image Classification by Hierarchical Spatial Pooling with Partial Least Squares Analysis." In British Machine Vision Conference 2012. British Machine Vision Association, 2012. http://dx.doi.org/10.5244/c.26.102.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Reports on the topic "Partial least squares analysis"

1

DREWIEN, CELESTE A. A Parallel Prediction-Augmented Classical Least Squares/Partial Least Squares Hybrid Algorithm: CPLS 1.0 Code. Office of Scientific and Technical Information (OSTI), June 2000. http://dx.doi.org/10.2172/759455.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Faber, V. Partial least squares, conjugate gradient and the fisher discriminant. Office of Scientific and Technical Information (OSTI), December 1996. http://dx.doi.org/10.2172/431144.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Hess, David E., and William E. Smith. Uncertainty Analysis Applied to Least Squares Curve and Surface Fits. Fort Belvoir, VA: Defense Technical Information Center, December 1998. http://dx.doi.org/10.21236/ada360063.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Luk, Franklin T., and Sanzheng Qiao. Analysis of a Linearly Constrained Least Squares Algorithm for Adaptive Beamforming. Fort Belvoir, VA: Defense Technical Information Center, August 1992. http://dx.doi.org/10.21236/ada255017.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Luk, Franklin T., and Sanzheng Qiao. Analysis of a Linearly Constrained Least Squares Algorithm for Adaptive Beamforming. Fort Belvoir, VA: Defense Technical Information Center, August 1992. http://dx.doi.org/10.21236/ada256509.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Lau, D. L., and L. C. Ng. Analysis of total least squares in estimating the parameters of a mortar trajectory. Office of Scientific and Technical Information (OSTI), December 1994. http://dx.doi.org/10.2172/96640.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Chervenkov, Hristo, and Kiril Slavov. Theil–Sen Estimator vs. Ordinary Least Squares — Trend Analysis for Selected ETCCDI Climate Indices. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, February 2018. http://dx.doi.org/10.7546/crabs.2019.01.06.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Blaha, Georges. Analysis of the Nonlinear Parametric Least-Squares Adjustment via an Isomorphic Geometrical Setup with Tensor Structure. Fort Belvoir, VA: Defense Technical Information Center, June 1988. http://dx.doi.org/10.21236/ada208219.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Carroll, Raymond J., P. Gallo, and L. J. Gleser. Comparisons of Least Squares and Errors-in-Variables Regression, with Special Reference to Randomized Analysis of Covariance. Fort Belvoir, VA: Defense Technical Information Center, September 1985. http://dx.doi.org/10.21236/ada160967.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Blumberg, L. N. Analysis of magnetic measurement data by least squares fit to series expansion solution of 3-D Laplace equation. Office of Scientific and Technical Information (OSTI), March 1992. http://dx.doi.org/10.2172/10185838.

Full text
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Partial least squares analysis' for particular source types:
Journal articles Dissertations / Theses Books
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography