psvalid

Checks, if a given regression function is adequate with respect to the partial sum criterium.

regression

nonparametric

model

Implementation of the SSR-Algorithm. The Sign-Simplicity-Regression model is a nonparametric statistical model which is based on residual signs and simplicity assumptions on the regression function. Goal is to calculate the most parsimonious regression function satisfying the statistical adequacy requirements. Theory and functions are specified in Metzner (2020, ISBN: 979-8-68239-420-3, "Trendbasierte Prognostik") and Metzner (2021, ISBN: 979-8-59347-027-0, "Adäquates Maschinelles Lernen").

Lars Metzner

sisireg

Sign-Simplicity-Regression-Solver

psvalid function

<dl> <dt>dat</dt>
<dd>obervations.</dd> <dt>mu</dt>
<dd>discrete regression function.</dd></dl>

Arguments

Author

Partial Sum Validity Check — psvalid

<dl>

 <dt>dat</dt>
<dd>obervations.</dd>

 <dt>mu</dt>
<dd>discrete regression function.</dd>

</dl>

psvalid: Partial Sum Validity Check

Description

Usage

Value

Arguments

Author

References

Examples