https://manuals.pqstat.pl/ 2026-05-01T17:35:46+00:00 https://manuals.pqstat.pl/ https://manuals.pqstat.pl/lib/tpl/dokuwiki/images/favicon.ico text/html 2022-02-11T12:08:07+00:00 Anonymous (anonymous@undisclosed.example.com) https://manuals.pqstat.pl/en:statpqpl:plotpl:bladpl Bland-Altman plot As noted by Bland and Altman (1986, 1999) in clinical medicine, measurements made on the living body are constantly changing and their true value is unknown (e.g., blood pressure), necessitating constant refinement and development of new and better tools to measure them. Usually, when a new method is created, its results are compared with another recognized method, the so-called gold standard. For this purpose, the compatibility of the new method with the previously used metho… text/html 2022-02-09T14:50:35+00:00 Anonymous (anonymous@undisclosed.example.com) https://manuals.pqstat.pl/en:statpqpl:plotpl:galpl Plot gallery text/html 2022-02-11T18:00:23+00:00 Anonymous (anonymous@undisclosed.example.com) https://manuals.pqstat.pl/en:statpqpl:plotpl:kde1pl Kernel estimation One-dimensional kernel estimator The one-dimensional kernel density estimator allows you to approximate the density of a data distribution by creating a smoothed density curve in a non-parametric way. It provides a better density estimate than is given by a traditional histogram, which columns form a staircase function. text/html 2022-02-11T11:27:07+00:00 Anonymous (anonymous@undisclosed.example.com) https://manuals.pqstat.pl/en:statpqpl:plotpl:lowess Local linear smoothing techniques LOWESS LOWESS (locally weighted scatterplot smoothing) also known as LOESS (locally estimated scatterplot smoothing) is one of many „modern” modeling methods based on the least squares method. LOESS combines the simplicity of linear regression with the flexibility of nonlinear regression. Locally weighted regression (LOESS) was independently introduced in several different fields in the late 19th and early 20th centuries (Henderson, 1916 text/html 2022-02-11T12:12:36+00:00 Anonymous (anonymous@undisclosed.example.com) https://manuals.pqstat.pl/en:statpqpl:plotpl:mackorel Correlation matrix When we are interested in correlation between many variables, a convenient way to visualize it is to present correlation coefficients in the form of a chart. Depending on the scale on which the data was collected, in PQStat we have a choice of these coefficients: