Some of you may have come across a growing number of publications in your field using an alternative paradigm called Bayesian statistics in which to perform their statistical analyses. The goal of ...

Bayesian quantile regression and statistical modelling represent a growing paradigm in contemporary data analysis, extending conventional regression by estimating various conditional quantiles rather ...

Fuzzy regression models extend traditional statistical regression by integrating fuzzy set theory to better handle imprecision and uncertainty inherent in many real-world data sets. These models ...

Python has some wonderful libraries for statistical analysis, but they might be overkill for simple tasks. The built-in statistics library might be what you want instead. Here are some things you can ...

This is a preview. Log in through your library . Abstract We consider quadratic regression models where the explanatory variable is measured with error. The effect of ...

The calibration method PLS1 is described in terms of the joint covariance structure of the explanatory variables and the predicted variable. In the population version it is possible to give simple ...

Linear regression is a powerful and long-established statistical tool that is commonly used across applied sciences, economics and many other fields. Linear regression considers the relationship ...

When you use the statistical analysis features in Excel, you are leveraging one of the most powerful tools available for data manipulation and interpretation. Excel is not just a spreadsheet ...