Problems in Regression 来自 SSRN 喜欢 0 阅读量: 21 作者: PE Pfeifer 摘要: These problems provide a general introduction to the basic concepts of single and multiple regressions. Topics covered include heteroskedasticity, autocorrelati 关键词: regression analysis DOI: 10.2139/ssrn.1422930 年份:...
Multicollinearity or linear dependence among the vectors of regressor variables in a multiple linear regression analysis can have sever effects on the estimation of parameters and on variables selection techniques. This expository paper examines the sources of multicollinearity and discusses some of its har...
Estimates of the regression coefficients which are unbiased and linear in the observations are discussed in this paper. The residual is assumed to be a stationary process. Two specific estimates are discussed, the least-squares estimate and the Markov estimate. I call the estimate which is ...
Mark D M.Some problems with the use of regression analysis in geography.Spatial Statistics and Models. 1984Mark D M. Some problems with the use of regression analysis in geography[A].Dreidel Publishing Company,Netherlands 1984.Mark D M. Some problems with the use of regression analysis in ...
We consider approximate methods of analysis of regression problems subject to errors in the predictor variables. In computational terms, these methods are related to the ordinary least squares method, which substantially simplifies the development of appropriate software. We consider approximate methods of...
In this paper, we consider two typical problems name: of multicollinearity among predictor variables and linear predictor link function in the analysis of longitudinal non-normal data. For the former, we employ ridge regression and for the later we adopt the use of B-splines for nonparametric com...
Regression shrinkage and selection via the lasso.Journal of the Royal Statistical Society, Series B58: 267–288. Ronan Conroy’s comments: I am struck by the fact that Judd and McClelland in their excellent bookData Analysis: A Model Comparison Approach(Harcourt Brace Jovanovich, ISBN 0-15-516...
Multicollinearity often causes a huge explanatory problem in regression analysis. In presence of multicollinearity, Ordinary Least Squares (OLS) regression may result in high variability in estimates of the regression coefficients in the presence of multicollinearity. Besides multicollinearity, outliers also ...
Exploratory Data Analysis (EDA) Feature Selection Linear Regression withsklearn Linear Regression withstatsmodels Advanced Regression techniques withsklearn 📑Logistic Regression In the case of logistic regressionYis a categorical value (0or1) and it is modeled as: ...
Logistic regression analysis demonstrated that older age, higher body mass index, a distorted body image, obsessive-compulsive tendency, and some familial issues were independently related to the eating problems. Discussion The prevalence of eating problems in the Japanese female population was low ...