ts.rnorm: Time Series Normal Distribution

In efriedland/friedland: Making Functions Do Your Econometrics For You

Description

Used the Normal Distribution function to generate random monthly time series datasets that end on the current date.

Usage

 ts.rnorm(n, mean = 0, sd = 1, initial, allownegatives = TRUE)

Arguments

n	number of observations. If length(n) > 1, the length is taken to be the number required.
mean	vector of means.
sd	vector of standard deviations.
initial	numeric; provides the initial value for the time series variable.
allownegatives	logical; if TRUE (default), negative values remain otherwise, negative values are replaced with 0.

Details

If mean or sd are not specified they assume the default values of 0 and 1, respectively.

Value

ts.rnorm generates random deviates.

See Also

rnorm

Examples

foo1 <- ts.rnorm(n = 150, mean = 0.01, initial = 100)
foo2 <- ts.rnorm(n = 150, mean = 0.01, initial = 283)
foo3 <- ts.rnorm(n = 150, mean = 0.01, initial = 44)
plot(cbind(foo1,foo2,foo3), ylab = "Price", main = "Random Time Series Variables")

efriedland/friedland documentation built on Feb. 9, 2021, 11:53 a.m.