Andere Kunden interessierten sich auch für
![Statistical Methods for Dynamic Models with Application]( "Statistical Methods for Dynamic Models with Application")
Statistical Methods for Dynamic Models with Application32,99 €![Selected Statistical Models in Non-Life Insurance with R]( "Selected Statistical Models in Non-Life Insurance with R")
Selected Statistical Models in Non-Life Insurance with R34,99 €![Linear Regression Models with Heteroscedastic Errors]( "Linear Regression Models with Heteroscedastic Errors")
Linear Regression Models with Heteroscedastic Errors53,99 €![Testing Restrictions In Linear Statistical Models]( "Testing Restrictions In Linear Statistical Models")
Testing Restrictions In Linear Statistical Models36,99 €![Inference in Linear Models With Auto Correlated Disturbances]( "Inference in Linear Models With Auto Correlated Disturbances")
Inference in Linear Models With Auto Correlated Disturbances40,99 €![Statistical Models for Customer Relationship Management]( "Statistical Models for Customer Relationship Management")
Statistical Models for Customer Relationship Management45,99 €![Estimation of Panel Data Models with Individual Effects]( "Estimation of Panel Data Models with Individual Effects")
Estimation of Panel Data Models with Individual Effects36,99 €
In this study, a variety of statistical models of regression type is considered. In some models observations are to be added by the respective design points if the latter are observable. Our models contain discontinuities of the response functions. In the case of a one-dimensional factor - an input variable - these discontinuities are presented by some change points. In the multivariate factor models, the discontinuities become functions. In either case, the principal objective of the statistical estimation is this discontinuity, a point or a function. Another feature of our models is that they may include a nuisance parameter. Typically, the dimension of the nuisance parameter grows proportionally to the number of observations. The nuisance parameter can be deterministic or stochastic. In the latter case, it is governed by a stochastic process. The statistical analysis in our study is asymptotical as the sample size increases to infinity.