| BasicStatistics {fBasics} | R Documentation |
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:
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:
stdev | Returns the standard deviation of a vector or matrix. |
stdev(x, na.rm = FALSE)
skewness(x, ...)
## Default S3 method:
skewness(x, na.rm = FALSE, method = c("moment", "fisher"), ...)
## S3 method for class 'data.frame':
skewness(x, ...)
## S3 method for class 'POSIXct':
skewness(x, ...)
## S3 method for class 'POSIXlt':
skewness(x, ...)
kurtosis(x, ...)
## Default S3 method:
kurtosis(x, na.rm = FALSE, method = c("excess", "moment", "fisher"), ...)
## S3 method for class 'data.frame':
kurtosis(x, ...)
## S3 method for class 'POSIXct':
kurtosis(x, ...)
## S3 method for class 'POSIXlt':
kurtosis(x, ...)
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, ...)
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 |
[colStats][rowStats - the statistical function to be applied. |
na.rm |
a logical. Should missing values be removed? |
method |
[kurtosis][skewness] - a character string which specifies the method of computation. These are either "moment" or "fisher", kurtosis
allows in addition for "excess". If "excess" is
selected, then the value of the kurtosis is computed by the
"moment" method and a value of 3 will be subtracted.
The "moment" method is based on the definitions of
skewness and kurtosis for distributions; these forms should
be used when resampling (bootstrap or jackknife). The
"fisher" method correspond to the usual "unbiased"
definition of sample variance, although in the case of skewness
and kurtosis exact unbiasedness is not possible.
|
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. |
skewness
kurtosis
return the value of the statistics, a numeric value. An
attribute which reports the used method is added.
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
compute sample statistics by column. Missing values can be
handled.
colStats
colAvgs
colVars
colStdevs,
colSkewness
colKurtosis
colCumsum
compute sample statistics by column. Missing values can be
handled.
R's-base package contains a function colMeans with an
additional argument dim=1. Therefore, the function used
here to compute column means (averages) is named colAvgs.
The function stdev computes the standard deviation for a
vector or matrix and was introduced for SPlus compatibility.
Under R use the function sd.
Diethelm Wuertz for the Rmetrics R-port.
## SOURCE("fBasics.15A-BasicStatistics")
## basicStats -
xmpBasics("\nStart: Basic Statistics of log-Returns > ")
# Data NYSE Composite Index:
data(nyseres)
basicStats(nyseres)
## mean -
## var -
## skewness -
## kurtosis -
xmpBasics("\nNext: Moments, Skewness and Kurtosis > ")
# Mean, Variance:
mean(nyseres)
var(nyseres)
# Skewness, Kurtosis:
class(nyseres)
skewness(nyseres[, 1])
kurtosis(nyseres[, 1])