Bibliographies thématiques / Heteroscedastic Multivariate Linear Regression / Articles de revues

Articles de revues sur le sujet « Heteroscedastic Multivariate Linear Regression »

Pour voir les autres types de publications sur ce sujet consultez le lien suivant : Heteroscedastic Multivariate Linear Regression.
Auteur : Grafiati
Publié le 10 mars 2023

Créez une référence correcte selon les styles APA, MLA, Chicago, Harvard et plusieurs autres

Choisissez une source :

Consultez les 50 meilleurs articles de revues pour votre recherche sur le sujet « Heteroscedastic Multivariate Linear Regression ».

À côté de chaque source dans la liste de références il y a un bouton « Ajouter à la bibliographie ». Cliquez sur ce bouton, et nous générerons automatiquement la référence bibliographique pour la source choisie selon votre style de citation préféré : APA, MLA, Harvard, Vancouver, Chicago, etc.

Vous pouvez aussi télécharger le texte intégral de la publication scolaire au format pdf et consulter son résumé en ligne lorsque ces informations sont inclues dans les métadonnées.

Parcourez les articles de revues sur diverses disciplines et organisez correctement votre bibliographie.

1

Zhang, X., C. E. Lee et X. Shao. « Envelopes in multivariate regression models with nonlinearity and heteroscedasticity ». Biometrika 107, no 4 (17 juin 2020) : 965–81. http://dx.doi.org/10.1093/biomet/asaa036.

Texte intégral
Résumé :
Summary Envelopes have been proposed in recent years as a nascent methodology for sufficient dimension reduction and efficient parameter estimation in multivariate linear models. We extend the classical definition of envelopes in Cook et al. (2010) to incorporate a nonlinear conditional mean function and a heteroscedastic error. Given any two random vectors ${X}\in\mathbb{R}^{p}$ and ${Y}\in\mathbb{R}^{r}$, we propose two new model-free envelopes, called the martingale difference divergence envelope and the central mean envelope, and study their relationships to the standard envelope in the context of response reduction in multivariate linear models. The martingale difference divergence envelope effectively captures the nonlinearity in the conditional mean without imposing any parametric structure or requiring any tuning in estimation. Heteroscedasticity, or nonconstant conditional covariance of ${Y}\mid{X}$, is further detected by the central mean envelope based on a slicing scheme for the data. We reveal the nested structure of different envelopes: (i) the central mean envelope contains the martingale difference divergence envelope, with equality when ${Y}\mid{X}$ has a constant conditional covariance; and (ii) the martingale difference divergence envelope contains the standard envelope, with equality when ${Y}\mid{X}$ has a linear conditional mean. We develop an estimation procedure that first obtains the martingale difference divergence envelope and then estimates the additional envelope components in the central mean envelope. We establish consistency in envelope estimation of the martingale difference divergence envelope and central mean envelope without stringent model assumptions. Simulations and real-data analysis demonstrate the advantages of the martingale difference divergence envelope and the central mean envelope over the standard envelope in dimension reduction.
Styles APA, Harvard, Vancouver, ISO, etc.
2

Shao, Jun, et J. N. K. Rao. « Jackknife inference for heteroscedastic linear regression models ». Canadian Journal of Statistics 21, no 4 (décembre 1993) : 377–95. http://dx.doi.org/10.2307/3315702.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
3

Leslie, David S., Robert Kohn et David J. Nott. « A general approach to heteroscedastic linear regression ». Statistics and Computing 17, no 2 (30 janvier 2007) : 131–46. http://dx.doi.org/10.1007/s11222-006-9013-8.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
4

Su, Li Yun, et Chun Hua Wang. « Two-Stage Local Polynomial Regression Method for Image Heteroscedastic Noise Removal ». Advanced Materials Research 860-863 (décembre 2013) : 2936–39. http://dx.doi.org/10.4028/www.scientific.net/amr.860-863.2936.

Texte intégral
Résumé :
In this paper, we introduce the extension of local polynomial fitting to the linear heteroscedastic regression model and its applications in digital image heteroscedastic noise removal. For better image noise removal with heteroscedastic energy, firstly, the local polynomial regression is applied to estimate heteroscedastic function, then the coefficients of regression model are obtained by using generalized least squares method. Due to non-parametric technique of local polynomial estimation, we do not need to know the heteroscedastic noise function. Therefore, we improve the estimation precision, when the heteroscedastic noise function is unknown. Numerical simulations results show that the proposed method can improve the image quality of heteroscedastic noise energy.
Styles APA, Harvard, Vancouver, ISO, etc.
5

Ounpraseuth, Songthip T., Phil D. Young, Johanna S. van Zyl, Tyler W. Nelson et Dean M. Young. « Linear Dimension Reduction for Multiple Heteroscedastic Multivariate Normal Populations ». Open Journal of Statistics 05, no 04 (2015) : 311–33. http://dx.doi.org/10.4236/ojs.2015.54033.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
6

Monteiro, Alessandra da Rocha Duailibe, Thiago de Sá Feital et José Carlos Pinto. « A Numerical Procedure for Multivariate Calibration Using Heteroscedastic Principal Components Regression ». Processes 9, no 9 (21 septembre 2021) : 1686. http://dx.doi.org/10.3390/pr9091686.

Texte intégral
Résumé :
Many methods have been developed to allow for consideration of measurement errors during multivariate data analyses. The incorporation of the error structure into the analytical framework, usually described in terms of the covariance matrix of measurement errors, can provide better model estimation and prediction. However, little effort has been made to evaluate the effects of heteroscedastic measurement uncertainties on multivariate analyses when the covariance matrix of measurement errors changes with the measurement conditions. For this reason, the present work describes a new numerical procedure for analyses of heteroscedastic systems (heteroscedastic principal component regression or H-PCR) that takes into consideration the variations of the covariance matrix of measurement fluctuations. In order to illustrate the proposed approach, near infrared (NIR) spectra of xylene and toluene mixtures were measured at different temperatures and stirring velocities and the obtained data were used to build calibration models with different multivariate techniques, including H-PCR. Modeling of available xylene–toluene NIR data revealed that H-PCR can be used successfully for calibration purposes and that the principal directions obtained with the proposed approach can be quite different from the ones calculated through standard PCR, when heteroscedasticity is disregarded explicitly.
Styles APA, Harvard, Vancouver, ISO, etc.
7

Thinh, Raksmey, Klairung Samart et Naratip Jansakul. « Linear regression models for heteroscedastic and non-normal data ». ScienceAsia 46, no 3 (2020) : 353. http://dx.doi.org/10.2306/scienceasia1513-1874.2020.047.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
8

Gijbels, I., et I. Vrinssen. « Robust estimation and variable selection in heteroscedastic linear regression ». Statistics 53, no 3 (18 février 2019) : 489–532. http://dx.doi.org/10.1080/02331888.2019.1579215.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
9

Linke, Yu Yu. « Two-Step Estimation in a Heteroscedastic Linear Regression Model ». Journal of Mathematical Sciences 231, no 2 (27 avril 2018) : 206–17. http://dx.doi.org/10.1007/s10958-018-3816-y.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
10

Faraway, Julian J., et Jiayang Sun. « Simultaneous Confidence Bands for Linear Regression with Heteroscedastic Errors ». Journal of the American Statistical Association 90, no 431 (septembre 1995) : 1094–98. http://dx.doi.org/10.1080/01621459.1995.10476612.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
11

Kuk, Anthony Y. C. « Nonparametrically Weighted Least Squares Estimation in Heteroscedastic Linear Regression ». Biometrical Journal 41, no 4 (juillet 1999) : 401–10. http://dx.doi.org/10.1002/(sici)1521-4036(199907)41:4<401 ::aid-bimj401>3.0.co;2-5.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
12

Su, Liyun, Yanyong Zhao et Tianshun Yan. « Two-Stage Method Based on Local Polynomial Fitting for a Linear Heteroscedastic Regression Model and Its Application in Economics ». Discrete Dynamics in Nature and Society 2012 (2012) : 1–17. http://dx.doi.org/10.1155/2012/696927.

Texte intégral
Résumé :
We introduce the extension of local polynomial fitting to the linear heteroscedastic regression model. Firstly, the local polynomial fitting is applied to estimate heteroscedastic function, then the coefficients of regression model are obtained by using generalized least squares method. One noteworthy feature of our approach is that we avoid the testing for heteroscedasticity by improving the traditional two-stage method. Due to nonparametric technique of local polynomial estimation, we do not need to know the heteroscedastic function. Therefore, we can improve the estimation precision, when the heteroscedastic function is unknown. Furthermore, we focus on comparison of parameters and reach an optimal fitting. Besides, we verify the asymptotic normality of parameters based on numerical simulations. Finally, this approach is applied to a case of economics, and it indicates that our method is surely effective in finite-sample situations.
Styles APA, Harvard, Vancouver, ISO, etc.
13

Kirlitsa, Valery P. « Construction D-optimal designs of experiments for linear multiple regression with heteroscedastic observations ». Journal of the Belarusian State University. Mathematics and Informatics, no 2 (12 juillet 2019) : 27–33. http://dx.doi.org/10.33581/2520-6508-2019-2-27-33.

Texte intégral
Résumé :
In article the problem of construction exact D-optimal designs of experiments for linear multiple regression in a case when variance of errors of observations depend on a point in which is made is investigated. Class of functions which describe change variance of heteroscedastic observations is defined for which it is possible construct D-optimal continues designs of experiments. For linear multiple regression with three factors it is constructed five different types of D-optimal continues designs of experiments with heteroscedastic observations. For each of these types the own class of functions describing change variance of observations is defined.
Styles APA, Harvard, Vancouver, ISO, etc.
14

Dorfman, Alan. « A note on millers's empirical weights for heteroscedastic linear regression ». Communications in Statistics - Theory and Methods 17, no 10 (janvier 1988) : 3521–35. http://dx.doi.org/10.1080/03610928808829818.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
15

Shen, Silian, et Changlin Mei. « Estimation of the Variance Function in Heteroscedastic Linear Regression Models ». Communications in Statistics - Theory and Methods 38, no 7 (24 mars 2009) : 1098–112. http://dx.doi.org/10.1080/03610920802374061.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
16

Schick, Anton. « Efficient estimates in linear and nonlinear regression with heteroscedastic errors ». Journal of Statistical Planning and Inference 58, no 2 (mars 1997) : 371–87. http://dx.doi.org/10.1016/s0378-3758(96)00077-8.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
17

You, Jinhong, Gemai Chen et Yong Zhou. « Statistical inference of partially linear regression models with heteroscedastic errors ». Journal of Multivariate Analysis 98, no 8 (septembre 2007) : 1539–57. http://dx.doi.org/10.1016/j.jmva.2007.06.011.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
18

Molstad, Aaron J., et Adam J. Rothman. « Indirect multivariate response linear regression ». Biometrika 103, no 3 (24 août 2016) : 595–607. http://dx.doi.org/10.1093/biomet/asw034.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
19

Andronov, Alexander. « Markov-modulated multivariate linear regression ». Acta et Commentationes Universitatis Tartuensis de Mathematica 21, no 1 (3 juillet 2017) : 43. http://dx.doi.org/10.12697/acutm.2017.21.03.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
20

Kirlitsa, Valery P. « D-optimal experimental designs for linear multiple regression under heteroscedastic observations ». Journal of the Belarusian State University. Mathematics and Informatics, no 2 (30 juillet 2020) : 59–67. http://dx.doi.org/10.33581/2520-6508-2020-2-59-67.

Texte intégral
Résumé :
The problem of construction of «continuous» (number of observations is not fixed) and «exact» (number of observations is fixed) D-optimal experimental designs for linear multiple regression in the case when variance of errors of observations depends on regressor value is studied in this paper. Families of functions that determine heteroscedastic observations are found for which it is possible to construct «continuous» and «exact» D-optimal experimental designs. «Continuous» D-optimal experimental designs under four different types of heteroscedasticity are constructed for linear multiple regression with three regressors.
Styles APA, Harvard, Vancouver, ISO, etc.
21

Muhammad, Faqir, Muhammad Aslam et G. R. Pasha. « Adaptive Estimation of Heteroscedastic Linear Regression Model Using Probability Weighted Moments ». Journal of Modern Applied Statistical Methods 7, no 2 (1 novembre 2008) : 501–5. http://dx.doi.org/10.22237/jmasm/1225512840.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
22

Inoue, Kiyoshi. « Iterative weighted least-squares estimates in a heteroscedastic linear regression model ». Journal of Statistical Planning and Inference 110, no 1-2 (janvier 2003) : 133–46. http://dx.doi.org/10.1016/s0378-3758(01)00285-3.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
23

Alshaybawee, Taha, Rahim Alhamzawi, Habshah Midi et Intisar Ibrahim Allyas. « Bayesian variable selection and coefficient estimation in heteroscedastic linear regression model ». Journal of Applied Statistics 45, no 14 (7 février 2018) : 2643–57. http://dx.doi.org/10.1080/02664763.2018.1432576.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
24

Dorugade, Ashok Vithoba. « Improved Ridge Estimator in Linear Regression with Multicollinearity, Heteroscedastic Errors and Outliers ». Journal of Modern Applied Statistical Methods 15, no 2 (1 novembre 2016) : 362–81. http://dx.doi.org/10.22237/jmasm/1478002860.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
25

Holmes, C. C., et B. K. Mallick. « Bayesian regression with multivariate linear splines ». Journal of the Royal Statistical Society : Series B (Statistical Methodology) 63, no 1 (février 2001) : 3–17. http://dx.doi.org/10.1111/1467-9868.00272.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
26

Cook, R. Dennis, et Xin Zhang. « Simultaneous Envelopes for Multivariate Linear Regression ». Technometrics 57, no 1 (2 janvier 2015) : 11–25. http://dx.doi.org/10.1080/00401706.2013.872700.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
27

Eck, Daniel J. « Bootstrapping for multivariate linear regression models ». Statistics & ; Probability Letters 134 (mars 2018) : 141–49. http://dx.doi.org/10.1016/j.spl.2017.11.001.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
28

Chiou, Jeng-Min, Ya-Fang Yang et Yu-Ting Chen. « Multivariate functional linear regression and prediction ». Journal of Multivariate Analysis 146 (avril 2016) : 301–12. http://dx.doi.org/10.1016/j.jmva.2015.10.003.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
29

Rodríguez del Águila, M. M., et N. Benítez-Parejo. « Simple linear and multivariate regression models ». Allergologia et Immunopathologia 39, no 3 (mai 2011) : 159–73. http://dx.doi.org/10.1016/j.aller.2011.02.001.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
30

Beyad, Yaser, et Marcel Maeder. « Multivariate linear regression with missing values ». Analytica Chimica Acta 796 (septembre 2013) : 38–41. http://dx.doi.org/10.1016/j.aca.2013.08.027.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
31

Lee, Yi-Tzu, et Thomas Mathew. « Tolerance regions in multivariate linear regression ». Journal of Statistical Planning and Inference 126, no 1 (novembre 2004) : 253–71. http://dx.doi.org/10.1016/j.jspi.2003.07.002.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
32

Wörz, Sascha, et Heinz Bernhardt. « A note on multivariate linear regression ». Communications in Statistics - Theory and Methods 47, no 19 (13 mars 2018) : 4785–90. http://dx.doi.org/10.1080/03610926.2018.1445863.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
33

Vicari, Donatella, et Maurizio Vichi. « Multivariate linear regression for heterogeneous data ». Journal of Applied Statistics 40, no 6 (juin 2013) : 1209–30. http://dx.doi.org/10.1080/02664763.2013.784896.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
34

Li, Xiongya, Xiuqin Bai et Weixing Song. « Robust mixture multivariate linear regression by multivariate Laplace distribution ». Statistics & ; Probability Letters 130 (novembre 2017) : 32–39. http://dx.doi.org/10.1016/j.spl.2017.06.028.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
35

Feigelson, E. D., et G. J. Babu. « Statistical Methodology for Large Astronomical Surveys ». Symposium - International Astronomical Union 179 (1998) : 363–70. http://dx.doi.org/10.1017/s0074180900129043.

Texte intégral
Résumé :
Multiwavelength surveys present a variety of challenging statistical problems: raw data processing, source identification, source characterization and classification, and interrelations between multiwavelength properties. For these last two issues, we discuss the applicability of standard and new multivariate statistical techniques. Traditional methods such as ANOVA, principal components analysis, cluster analysis, and tests for multivariate linear hypotheses are underutilized in astronomy and can be very helpful. Newer statistical methods such as projection pursuit, multivariate splines, and visualization tools such as XGobi are briefly introduced. However, multivariate databases from astronomical surveys present significant challenges to the statistical community. These include treatments of heteroscedastic measurement errors, censoring and truncation due to flux limits, and parameter estimation for nonlinear astrophysical models.
Styles APA, Harvard, Vancouver, ISO, etc.
36

Hsiao, Chih-Wen, Ya-Chuan Chan, Mei-Yu Lee et Hsi-Peng Lu. « Heteroscedasticity and Precise Estimation Model Approach for Complex Financial Time-Series Data : An Example of Taiwan Stock Index Futures before and during COVID-19 ». Mathematics 9, no 21 (26 octobre 2021) : 2719. http://dx.doi.org/10.3390/math9212719.

Texte intégral
Résumé :
In this paper, we provide a mathematical and statistical methodology using heteroscedastic estimation to achieve the aim of building a more precise mathematical model for complex financial data. Considering a general regression model with explanatory variables (the expected value model form) and the error term (including heteroscedasticity), the optimal expected value and heteroscedastic model forms are investigated by linear, nonlinear, curvilinear, and composition function forms, using the minimum mean-squared error criterion to show the precision of the methodology. After combining the two optimal models, the fitted values of the financial data are more precise than the linear regression model in the literature and also show the fitted model forms in the example of Taiwan stock price index futures that has three cases: (1) before COVID-19, (2) during COVID-19, and (3) the entire observation time period. The fitted mathematical models can apparently show how COVID-19 affects the return rates of Taiwan stock price index futures. Furthermore, the fitted heteroscedastic models also show how COVID-19 influences the fluctuations of the return rates of Taiwan stock price index futures. This methodology will contribute to the probability of building algorithms for computing and predicting financial data based on mathematical model form outcomes and assist model comparisons after adding new data to a database.
Styles APA, Harvard, Vancouver, ISO, etc.
37

Guney, Yesim, Olcay Arslan et Fulya Gokalp Yavuz. « Robust estimation in multivariate heteroscedastic regression models with autoregressive covariance structures using EM algorithm ». Journal of Multivariate Analysis 191 (septembre 2022) : 105026. http://dx.doi.org/10.1016/j.jmva.2022.105026.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
38

Fiorentini, Gabriele, Enrique Sentana et Giorgio Calzolari. « Maximum Likelihood Estimation and Inference in Multivariate Conditionally Heteroscedastic Dynamic Regression Models With StudenttInnovations ». Journal of Business & ; Economic Statistics 21, no 4 (octobre 2003) : 532–46. http://dx.doi.org/10.1198/073500103288619232.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
39

Das, Debraj, et S. N. Lahiri. « Distributional consistency of the lasso by perturbation bootstrap ». Biometrika 106, no 4 (30 juin 2019) : 957–64. http://dx.doi.org/10.1093/biomet/asz029.

Texte intégral
Résumé :
Summary The lasso is a popular estimation procedure in multiple linear regression. We develop and establish the validity of a perturbation bootstrap method for approximating the distribution of the lasso estimator in a heteroscedastic linear regression model. We allow the underlying covariates to be either random or nonrandom, and show that the proposed bootstrap method works irrespective of the nature of the covariates. We also investigate finite-sample properties of the proposed bootstrap method in a moderately large simulation study.
Styles APA, Harvard, Vancouver, ISO, etc.
40

Liang, Han-Ying, et Bing-Yi Jing. « Strong Consistency of Estimators for Heteroscedastic Partly Linear Regression Model under Dependent Samples ». Journal of Applied Mathematics and Stochastic Analysis 15, no 3 (1 janvier 2002) : 207–19. http://dx.doi.org/10.1155/s1048953302000187.

Texte intégral
Résumé :
In this paper we are concerned with the heteroscedastic regression model yi=xiβ+g(ti)+σiei, 1≤i≤n under correlated errors ei, where it is assumed that σi2=f(ui), the design points (xi,ti,ui) are known and nonrandom, and g and f are unknown functions. The interest lies in the slope parameter β. Assuming the unobserved disturbance ei are negatively associated, we study the issue of strong consistency for two different slope estimators: the least squares estimator and the weighted least squares estimator.
Styles APA, Harvard, Vancouver, ISO, etc.
41

Begum, Nelufa, et Maxwell L. King. « Most mean powerful test for testing heteroscedastic disturbances in the linear regression model ». Model Assisted Statistics and Applications 1, no 1 (15 décembre 2005) : 9–16. http://dx.doi.org/10.3233/mas-2006-1103.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
42

You, Jinhong, Xian Zhou et Yong Zhou. « Statistical inference for panel data semiparametric partially linear regression models with heteroscedastic errors ». Journal of Multivariate Analysis 101, no 5 (mai 2010) : 1079–101. http://dx.doi.org/10.1016/j.jmva.2010.01.003.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
43

Schick, Anton, et Yilin Zhu. « Maximum Empirical Likelihood Estimation In A Heteroscedastic Linear Regression ModelWith Possibly Missing Responses ». Sri Lankan Journal of Applied Statistics 5, no 4 (15 décembre 2014) : 209. http://dx.doi.org/10.4038/sljastats.v5i4.7791.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
44

Wilcox, Rand R. « Linear regression : robust heteroscedastic confidence bands that have some specified simultaneous probability coverage ». Journal of Applied Statistics 44, no 14 (24 novembre 2016) : 2564–74. http://dx.doi.org/10.1080/02664763.2016.1257591.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
45

EA, Emrah Altun, Morad Alizadeh, Thiago Ramires et Edwin Ortega. « Generalized Odd Power Cauchy Family and Its Associated Heteroscedastic Regression Model ». Statistics, Optimization & ; Information Computing 9, no 3 (10 juillet 2021) : 516–28. http://dx.doi.org/10.19139/soic-2310-5070-765.

Texte intégral
Résumé :
This study introduces a generalization of the odd power Cauchy family by adding one more shape parameter togain more flexibility modeling the complex data structures. The linear representations for the density, moments, quantile,and generating functions are derived. The model parameters are estimated employing the maximum likelihood estimationmethod. The Monte Carlo simulations are performed under different parameter settings and sample sizes for the proposedmodels. In addition, we introduce a new heteroscedastic regression model based on the special member of the proposedfamily. Three data sets are analyzed with competitive and proposed models.
Styles APA, Harvard, Vancouver, ISO, etc.
46

Orlandi, Manuel, Margarita Escudero-Casao et Giulia Licini. « Nucleophilicity Prediction via Multivariate Linear Regression Analysis ». Journal of Organic Chemistry 86, no 4 (3 février 2021) : 3555–64. http://dx.doi.org/10.1021/acs.joc.0c02952.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
47

Breiman, Leo, et Jerome H. Friedman. « Predicting Multivariate Responses in Multiple Linear Regression ». Journal of the Royal Statistical Society : Series B (Statistical Methodology) 59, no 1 (février 1997) : 3–54. http://dx.doi.org/10.1111/1467-9868.00054.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
48

Yang, L., et R. Tschernig. « Multivariate bandwidth selection for local linear regression ». Journal of the Royal Statistical Society : Series B (Statistical Methodology) 61, no 4 (novembre 1999) : 793–815. http://dx.doi.org/10.1111/1467-9868.00203.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
49

Liu, Wei, Yang Han, Fang Wan, Frank Bretz et Anthony J. Hayter. « Simultaneous Confidence Tubes in Multivariate Linear Regression ». Scandinavian Journal of Statistics 43, no 3 (17 mars 2016) : 879–85. http://dx.doi.org/10.1111/sjos.12217.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
50

Mantz, Adam B. « A Gibbs sampler for multivariate linear regression ». Monthly Notices of the Royal Astronomical Society 457, no 2 (1 février 2016) : 1279–88. http://dx.doi.org/10.1093/mnras/stv3008.

Texte intégral
Styles APA, Harvard, Vancouver, ISO, etc.
Vous pouvez également être intéressé par les bibliographies sur le sujet « Heteroscedastic Multivariate Linear Regression » pour d’autres types de sources :
Thèses Livres
Nous offrons des réductions sur tous les plans premium pour les auteurs dont les œuvres sont incluses dans des sélections littéraires thématiques. Contactez-nous pour obtenir un code promo unique!

Vers la bibliographie