Functions to compute row statistical properties of financial and economic time series data.

The functions are:

 rowStats calculates row statistics, rowSds calculates row standard deviations, rowVars calculates row variances, rowSkewness calculates row skewness, rowKurtosis calculates row kurtosis, rowMaxs calculates maximum values in each row, rowMins calculates minimum values in each row, rowProds computes product of all values in each row, rowQuantiles computes quantiles of each row.

## Usage

rowStats(x, FUN, ...)

<!-- % rowSums(x, \dots) -->
<!-- % rowMeans(x, \dots) -->

rowSds(x, ...)
rowVars(x, ...)
rowSkewness(x, ...)
rowKurtosis(x, ...)
rowMaxs(x, ...)
rowMins(x, ...)
rowProds(x, ...)
rowQuantiles(x, prob = 0.05, ...)

rowStdevs(x, ...)
rowAvgs(x, ...)

## Arguments

FUN

a function name, the statistical function to be applied.

prob

a numeric value, the probability with value in [0,1].

x

a rectangular object which can be transformed into a matrix by the function as.matrix.

...

arguments to be passed.

## Value

each function returns a numeric vector of the statistics

colStats

## Examples

## Simulated Return Data in Matrix Form:
x = matrix(rnorm(10*10), nrow = 10)

## rowStats -
rowStats(x, FUN = mean)
#>  [1]  0.18422758 -0.07130207  0.41613040  0.01773426  0.33939605  0.18244729
#>  [7]  0.19210571 -0.22218828  0.23648095 -0.14000824

## rowMaxs -
rowMaxs(x)
#>  [1] 1.8815871 0.6135046 1.4881833 1.6704000 2.9194556 2.4254361 1.7637915
#>  [8] 1.0885857 2.1724900 0.9874172