In the paper the estimation of sample median bias and variance by jackknife and bootstrap methods are considered. Monte Carlo analysis of properties of estimators is presented (mean of bias and mean of variance for some ...

In this study problems connected with the detection of influential observations are investigated in the linear regression model using the least squares estimation of structural parameters. This issue has been presented ...

In the paper we present the examples of forecasts of time series with seasonal fluctuations. Based on the jackknife method we estimate variances of seasonal factors and the MSE of prediction. Jackknife method has been ...

Multiple additive regression trees MART is a methodology for trying to solve prediction problems in regression and classification. It’s one of the boosting methods. It was introduced by J. H. Friedman (1999a). Besides ...

It became more important to recognize customer expectations and to oiler product properties, which convince customer to buy the analyzed product. In customer loyalty and satisfaction analysis methods, classification trees ...

In this paper an analysis of the time series on the Day Ahead Market (DAM) of the Polish Power Exchange is presented. In this analysis Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models are used to ...

In ANOVA we are mainly based on inter-treatment comparisons. Another common problems arising in biometric studies (especially in biomedical studies) is that of comparing two groups of patients (treatment and a control ...

The idea of error decomposition originates in regression where squared loss function is applied. More recently, several authors have proposed corresponding decompositions for classification problem, where 0-1 loss is ...

In this paper the quadratic form of sample mean, sample variance and sample asymmetry is considered. This quadratic form can be used for testing hypothesis on the expected value, variance and asymmetry of observed variable. ...