# R/deneqtest.R In np: Nonparametric Kernel Smoothing Methods for Mixed Data Types

#### Defines functions summary.deneqtestprint.deneqtestdeneqtest

```deneqtest <- function(Tn,
In,
Tn.bootstrap,
In.bootstrap,
Tn.P,
In.P,
boot.num) {

tdeneq = list(Tn=Tn,
In=In,
Tn.bootstrap=Tn.bootstrap,
In.bootstrap=In.bootstrap,
Tn.P=Tn.P,
In.P=In.P,
boot.num=boot.num)

reject <- ' '

if (Tn.P < 0.1)
reject <- '.'

if (Tn.P < 0.05)
reject <- '*'

if (Tn.P < 0.01)
reject <- '**'

if (Tn.P < 0.001)
reject <- '***'

tdeneq\$reject <- reject
tdeneq\$rejectNum <- switch(reject,
' ' = 100,
'.' = 10,
'*' = 5,
'**' = 1,
'***' = 0.1)

class(tdeneq) <- "deneqtest"

tdeneq
}

print.deneqtest <- function(x, ...){
cat("\nConsistent Density Equality Test",
paste("\n", format(x\$boot.num), " Bootstrap Replications",sep=""),
"\n\nTest Statistic ", sQuote("Tn"), ": ",
format(x\$Tn), "\tP Value: ", format.pval(x\$Tn.P)," ", x\$reject,
"\n---\nSignif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1",
ifelse(x\$reject == ' ', "\nFail to reject the null of equality at the 10% level",
paste("\nNull of equality is rejected at the ", x\$rejectNum, "% level", sep="")),
"\n\n", sep="")
}

summary.deneqtest <- function(object, ...){
print(object)
}
```

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np documentation built on March 31, 2023, 9:41 p.m.