We propose an observation-driven dynamic common factor model for missing value imputation in high-dimensional panel … point forecasts, but also density forecasts for the missing data, thus allowing the researcher to quantify imputation …

We propose an observation-driven dynamic common factor model for missing value imputation in high-dimensional panel … point forecasts, but also density forecasts for the missing data, thus allowing the researcher to quantify imputation …

. Findings are compared with particular cases and confidence intervals are used as a basic tool of comparison. Pattern imputation …

Incorrect data sets may bias statistical results. To avoid this, various processing, edi ting and imputation steps were …

Incorrect data sets may bias statistical results. To avoid this, various processing, edi ting and imputation steps were …

When faced with missing data in a statistical survey or administrative sources, imputation is frequently used in order …. This paper presents research on the efficiency of model-based imputation in business statistics, where the explanatory … types of similar techniques: ratio imputation, regression imputation, regression imputation with iteration, predictive mean …

procedure called imputation is applied, which uses the available data as a tool for the replacement of the missing values. Two … present the application of the Chain-type factor estimator as a means of source imputation for the non-response units in an …