Results 281 to 290 of about 2,842,066 (337)
Factor analysis regression [PDF]
Statistical Papers, 2006 In the presence of multicollinearity the literature points to principal component regression (PCR) as an estimation method for the regression coefficients of a multiple regression model. Due to ambiguities in the interpretation, involved by the orthogonal transformation of the set of explanatory variables, the method could not yet gain wide acceptance.
Kosfeld, Reinhold +1 more
openaire +2 more sources
Some of the next articles are maybe not open access.
Related searches:
Related searches:
2019
Linear regression models a dependent variable Y in terms of a linear combination of p independent variables X=[X1|...|Xp] and estimates the coefficients of the combination using independent observations (x_i,Y_i ),i=1,...,n. The Gauss-Markov conditions guarantees that the least squares estimate of the regression coefficients constitutes the best linear
ANGELINI, Claudia
openaire +2 more sources
Linear regression models a dependent variable Y in terms of a linear combination of p independent variables X=[X1|...|Xp] and estimates the coefficients of the combination using independent observations (x_i,Y_i ),i=1,...,n. The Gauss-Markov conditions guarantees that the least squares estimate of the regression coefficients constitutes the best linear
ANGELINI, Claudia
openaire +2 more sources
Logistic Regression Analysis [PDF]
, 1990 In chapter 8 the connection to log-linear models for contingency tables was stressed. The direct connection to regression analysis for continuous response variables will now be brought more clearly into focus. Assume as before that the response variable is binary and that it is observed together with p explanatory variables.
openaire +1 more source
1998
So far we have considered only one regressor X besides the constant in the regression equation. Economic relationships usually include more than one regressor. For example, a demand equation for a product will usually include real price of that product in addition to real income as well as real price of a competitive product and the advertising ...
openaire +2 more sources
So far we have considered only one regressor X besides the constant in the regression equation. Economic relationships usually include more than one regressor. For example, a demand equation for a product will usually include real price of that product in addition to real income as well as real price of a competitive product and the advertising ...
openaire +2 more sources
Regression Analysis and Multivariate Analysis
Seminars in Reproductive Medicine, 1996Proper evaluation of data does not necessarily require the use of advanced statistical methods; however, such advanced tools offer the researcher the freedom to evaluate more complex hypotheses. This overview of regression analysis and multivariate statistics describes general concepts. Basic definitions and conventions are reviewed.
David L. Olive, Antoni J. Duleba
openaire +3 more sources
2014
Regression resembles supervised learning: data instances with accompanying labels are provided for a learning algorithm. The key difference is that in a classification problem, the labels belong to a finite set, whereas in regression, the labels can take an arbitrary real value.
openaire +3 more sources
Regression resembles supervised learning: data instances with accompanying labels are provided for a learning algorithm. The key difference is that in a classification problem, the labels belong to a finite set, whereas in regression, the labels can take an arbitrary real value.
openaire +3 more sources
Regression-Discontinuity Analysis
2008The regression discontinuity (RD) data design is a quasi-experimental evaluation design first introduced by Thistlethwaite and Campbell (1960) as an alternative approach to evaluating social programmes. The design is characterized by a treatment assignment or selection rule which involves the use of a known cut-off point with respect to a continuous ...
openaire +2 more sources
Regression and Factor Analysis
Biometrika, 1973SUMMARY A basic model of factor analysis is employed in the estimation of multiple correlation coefficients and partial regression weights. Estimators are derived for situations in which some or all of the independent variates are subject to errors in measurement.
A. E. Maxwell, D. N. Lawley
openaire +3 more sources
Regression Analysis and Estimating Regression Models
2020A forecast is merely a prediction about the future values of data. Financial forecasts span a broad range of areas, and each of the forecasts is of interest to a number of people and departments in a firm. A sales manager may wish to forecast sales (either in units sold or revenues generated).
Mustafa Gultekin +2 more
openaire +2 more sources