raw_gen {TestDimorph} | R Documentation |
Raw Data Generation By Normal Or Truncated Normal Distribution
Description
Generates raw data from summary statistics using uni/multivariate truncated normal distribution
Usage
raw_gen(
x,
Trait = 1,
Pop = 2,
R.res = NULL,
lower = -Inf,
upper = Inf,
verbose = FALSE
)
Arguments
x |
Data frame or list containing summary statistics for multiple parameters measured in both sexes in two or more populations. |
Trait |
Number of the column containing names of measured parameters, Default: 1 |
Pop |
Number of the column containing populations' names, Default: 2 |
R.res |
Pooled within correlation matrix, Default: NULL |
lower |
scalar of lower bounds, Default: -Inf |
upper |
scalar of upper bounds, Default: Inf |
verbose |
Logical; if TRUE displays a message with the method used for generation , Default: FALSE |
Details
If data generation is desired using multivariate distribution data is entered in the form of a list of summary statistics and pooled within correlation matrix as in baboon.parms_list, or the summary statistics are entered separately in the form of a data frame as in baboon.parms_df with a separate correlation matrix as in baboon.parms_R. If data frame is entered without a correlation matrix, data generation is carried out using univariate distribution.
Value
a data frame of raw data
Examples
# Data generation using univariate distributions
raw_gen(baboon.parms_df, lower = 0)
# another univariate example
library(dplyr)
data <- Cremains_measurements[1, ] %>% mutate(Pop=c("A")) %>%
relocate(Pop,.after=1)
raw_gen(data)[, -2]
# Data generation using multivariate distribution
raw_gen(baboon.parms_list, lower = 0)