corranalysis: Correlation analysis

In BasketballAnalyzeR: Analysis and Visualization of Basketball Data

Description

Correlation analysis

Usage

corranalysis(data, threshold = 0, sig.level = 0.95)

Arguments

data	a numeric matrix or data frame (see cor).
threshold	numeric, correlation cutoff (default 0); correlations in absolute value below threshold are set to 0.
sig.level	numeric, significance level (default 0.95); correlations with p-values greater that 1-sig.level are set to 0.

Value

A list with the following elements:

• corr.mtx (the complete correlation matrix)

• corr.mtx.trunc (the truncated correlation matrix)

• cor.mtest (the output of the significance test on correlations; see cor.mtest)

• threshold correlation cutoff

• sig.level significance level

Author(s)

Marco Sandri, Paola Zuccolotto, Marica Manisera ([e-mail])

References

P. Zuccolotto and M. Manisera (2020) Basketball Data Science: With Applications in R. CRC Press.

See Also

plot.corranalysis.

Examples

data <- data.frame(Pbox$PTS,Pbox$P3M,Pbox$P2M,
                   Pbox$OREB + Pbox$DREB,Pbox$AST,
                   Pbox$TOV,Pbox$STL,Pbox$BLK)/Pbox$MIN
names(data) <- c("PTS","P3M","P2M","REB","AST","TOV","STL","BLK")
data <- subset(data, Pbox$MIN >= 500)
out <- corranalysis(data, threshold = 0.5)
plot(out)

BasketballAnalyzeR documentation built on July 2, 2020, 2:14 a.m.