fBasics (version 201.10060)

BasicStatistics: Basic Statistics Summary

Description

A collection and description of functions to compute basic statistical properties. Missing functions in R to calculate skewness and kurtosis are added, a function which creates a summary statistics, and functions to calculate column and row statistics. The functions are: ll{ skewness returns value of skewness, kurtosis returns value of kurtosis, basicStats computes an overview of basic statistical values, rowStats calculates row statistics, colStats calculates column statistics, rowAvgs calculates row means, colAvgs calculates column means, rowVars calculates row variances, colVars calculates column variances, rowStdevs calculates row standard deviations, colStdevs calculates column standard deviations, rowSkewness calculates row skewness, colSkewness calculates column skewness, rowKurtosis calculates row kurtosis, colKurtosis calculates column kurtosis, rowCumsums calculates row cumulated Sums, colCumsums calculates column cumulated Sums. } For SPLUS Compatibility: ll{ stdev Returns the standard deviation of a vector or matrix. }

Usage

skewness(x, ...)
## S3 method for class 'default':
skewness(x, na.rm = FALSE, \dots)
## S3 method for class 'data.frame':
skewness(x, \dots)
## S3 method for class 'POSIXct':
skewness(x, \dots)
## S3 method for class 'POSIXlt':
skewness(x, \dots)

kurtosis(x, ...)
## S3 method for class 'default':
kurtosis(x, na.rm = FALSE, \dots)
## S3 method for class 'data.frame':
kurtosis(x, \dots)
## S3 method for class 'POSIXct':
kurtosis(x, \dots)
## S3 method for class 'POSIXlt':
kurtosis(x, \dots)

basicStats(x, ci = 0.95, column = 1)

rowStats(x, FUN, na.rm = FALSE, ...) 
rowAvgs(x, na.rm = FALSE, ...)
rowVars(x, na.rm = FALSE, ...)
rowStdevs(x, na.rm = FALSE, ...)
rowSkewness(x, na.rm = FALSE, ...)
rowKurtosis(x, na.rm = FALSE, ...)
rowCumsums(x, na.rm = FALSE, ...)

colStats(x, FUN, na.rm = FALSE, ...) 
colAvgs(x, na.rm = FALSE, ...)
colVars(x, na.rm = FALSE, ...)
colStdevs(x, na.rm = FALSE, ...)
colSkewness(x, na.rm = FALSE, ...)
colKurtosis(x, na.rm = FALSE, ...)
colCumsums(x, na.rm = FALSE, ...)

stdev(x, na.rm = FALSE)

Arguments

ci

confidence interval, a numeric value, by default 0.95, i.e. 95 percent.

column

[basicStats] - which column should be selected from the input matrix, data frame or timeSeries object. By default an integer value set to 1.

FUN

the statistical function to be applied.

na.rm

a logical. Should missing values be removed?

x

a numeric vector, or a matrix for column statistics. [basicStats] - allows also a matrix, data.frame or timeSeries as input. In this case only the first column of data will be considered and a a warning will be printed.

...

arguments to be passed.

Value

• skewness, kurtosis returns the value of the statistics, a numeric value. basicsStats returns data frame with the following entries and row names: nobs, NAs, Minimum, Maximum , 1. Quartile, 3. Quartile, Mean, Median, Sum, SE Mean, LCL Mean, UCL Mean, Variance, Stdev, Skewness, Kurtosis. rowStats, rowAvgs, rowVars, rowStdevs, rowSkewness, rowKurtosis, rowCumsum computes sample statistics by column. Missing values can be handled. colStats, colAvgs, colVars, colStdevs, colSkewness, colKurtosis, colCumsum computes sample statistics by column. Missing values can be handled.

See Also

colMeans, mean, median, var.

Examples

## SOURCE("fBasics.A0-SPlusCompatibility")
## SOURCE("fBasics.A2-BasicStatistics")

## basicStats -
   xmpBasics("Start: Basic Statistics of log-Returns > ")
   # Data NYSE Composite Index:
   data(nyseres)
   basicStats(nyseres)  
     
## mean -
## var -
## skewness -
## kurtosis -
   xmpBasics("Next: Moments, Skewness and Kurtosis > ")
   # Mean, Variance:
   mean(nyseres)
   var(nyseres)
   # Skewness, Kurtosis:
   class(nyseres)
   skewness(nyseres[, 1])
   kurtosis(nyseres[, 1])