L_regress: Likelihood Support for Regression In likelihoodR: Likelihood Analyses for Common Statistical Tests

Description

This function calculates the supports for different regression fits from 2 vectors of data. Models include linear, quadratic and cubic (given sufficient data). A plot is included showing linear (black), quadratic (red) and cubic (blue dashed) lines. P values for tehe model fits are also given.

Usage

 `1` ```L_regress(y, x, verb=TRUE) ```

Arguments

 `y` a numeric vector the same length as x. `x` a numeric vector. `verb` show output, default = TRUE.

Value

\$S.LNc - corrected support for linear versus null model.

\$S.LN - uncorrected support for linear versus null model.

\$S.QLc - corrected support for quadratic versus linear model.

\$S.QL - uncorrected support for quadratic versus linear model.

S.QCc = support for quadratic versus cubic model.

\$N - sample size.

\$p.vals - p values for 3 fits.

References

Cahusac, P.M.B. (2020) Evidence-Based Statistics, Wiley, ISBN : 978-1119549802

Royall, R. M. (1997). Statistical evidence: A likelihood paradigm. London: Chapman & Hall, ISBN : 978-0412044113

Edwards, A.W.F. (1992) Likelihood, Johns Hopkins Press, ISBN : 978-0801844430

Examples

 ``` 1 2 3 4 5 6 7 8 9 10``` ```# for women's world record times for 1500m event example, p 108 years <- c(0.0, 7.1, 8.9, 8.9, 10.1, 12.8, 17.0, 19.1, 25.0, 28.7, 29.7, 29.9, 35.3, 39.8, 40.2, 41.9, 42.1, 44.0, 44.9, 45.0, 45.1, 45.1, 48.9, 52.9, 53.0, 66.1, 87.9) time <- c(5.30, 5.12, 5.03, 4.79, 4.75, 4.70, 4.63, 4.63, 4.62, 4.59, 4.50, 4.50, 4.32, 4.29, 4.26, 4.21, 4.18, 4.16, 4.12, 4.11, 4.09, 4.02, 3.93, 3.92, 3.87, 3.84, 3.83) m=L_regress(time, years) m ```

likelihoodR documentation built on Dec. 11, 2021, 9:42 a.m.