Department of StatisticsTaylor & FrancisStatisticsS. Sen Roy, S.N. Guria, Estimation of Regression Parameters in the Presence of Outliers in the Response, Statistics, 43,6(2009) 531-539.S. Sen Roy, S. Guria, Estimation of regression parameters in the presence of outliers in the response, ...
The regression model nonlinear in factors and having errors in the factor levels settings, is transformed into a model with all the errors being in the response. A method for estimation of the transformed model parameters is proposed provided that the moments of the errors in the factor levels ...
This paper examines a nontraditional theoretical approach to solving the problem of determining the sensitivity of materials to polychromatic light on the basis of experiments on the effect of solar or artificial polychromatic exposure. The approach is nontraditional in that the problem of determining the...
When you fit multivariate linear regression models usingmvregress, you can use the optional name-value pair'algorithm','cwls'to choose least squares estimation. In this case, by default,mvregressreturns ordinary least squares (OLS) estimates usingΣ=Id. Alternatively, if you specify a covariance ...
This lecture shows how to perform maximum likelihood estimation of the parameters of a linear regression model whose error terms are normally distributed conditional on the regressors. In order to fully understand the material presented here, it might be useful to revise the introductions to maximum ...
2.1 Simple Regression Model: A Second View Consider the same simple regression model: y = \beta_{0} + \beta_{1}x+u \tag*{} \beta_{0} and \beta_{1} are unknown parameters in the nature we want to uncover. I choose x. Nature (someone else) chooses u . Finally, y is determi...
Instead, we propose scale estimators that do not depend on any previous estimate of the regression parameters. For this purpose we consider triangles formed by data points, and define their vertical height. Taking the repeated median of all such heights leads to a 50% breakdown point estimator....
The random regression model (RRM) methodology was applied to the estimation of genetic parameters for cumulative egg numbers and monthly egg production in a broiler dam line. The data were extracted from records of a commercial dam line in 2001 to 2003. A total of 99,193 records from 6,475...
The d-variate FGM copula consists of [Math Processing Error]∑j=2d(dj)=2d−d−1 dependence parameters. The correlation and regression properties for any pair of UU were studied by Johnson and Kotz (1977). The joint density function of UU, denoted by cd, is given by [Math Processing ...
Parameters of a probability distribution, such as the mean and standard deviation of a normal distribution Regression coefficients of a regression model, such asY=a′X TheStatistics and Machine Learning Toolbox™supports these and similar parameter estimation tasks with more than 40 different probabili...