Create individual data frame from a covset object

Description

Create individual data frame from a covset object

Usage

as_idata(.covset, .n)

Arguments

Examples

cov1 <- covset(Y ~ rbinomial(0.2), Z ~ rnorm(2,2))

as_idata(cov1, 10)

Build a object or formula to use with covset.

Description

build_covform formulates then parses a formula that can be used in a covset. build_covobj just assembles the object directly.

Usage

build_covform(
  var,
  dist,
  args,
  lower = NULL,
  upper = NULL,
  by = NULL,
  envir = parent.frame()
)

build_covobj(
  var,
  dist,
  args,
  upper = NULL,
  lower = NULL,
  by = NULL,
  envir = parent.frame()
)

Arguments

Details

When length of var is greater than one, both lower and upper must be named vectors when specifiation is made. However, it is acceptable to specify nothing or to use unnamed limits when the lenght of var is 1.

Examples

build_covform("WT", "rnorm", c("mu = 80", "sd = 40"), lower = 40, upper = 140)
build_covform("WT", "rnorm", "80,40", lower = 40, upper = 140)

build_covobj("WT", "rnorm", "80,40", lower = 40, upper = 140)

Covobj and covset objects.

Description

Covobj and covset objects.

Create a set of covariates.

Usage

new_covobj(x, envir = parent.frame(), ...)

## S3 method for class 'covobj'
print(x, ...)

## S4 method for signature 'covobj'
as.list(x, ...)

## S4 method for signature 'covset'
as.list(x, ...)

## S3 method for class 'covset'
print(x, ...)

covset(..., envir = parent.frame())

rvset(...)

as.covset(x)

Arguments

Details

rvset is an alias for covset.

Examples

obj <- new_covobj(Y[0,80] ~ rnorm(20,50))

obj

as.list(obj)

a <- Y ~ runif(0,1)
b <- Z ~ rbeta(1,1)

set <- covset(a,b)

set

as.list(set)

mutate a data frame, adding random variables.

Description

mutate a data frame, adding random variables.

Apply formulae to a data frame

Usage

dmutate(data, ...)

Arguments

Examples

idata <- dplyr::data_frame(ID = 1:10)

dmutate(idata, y ~ rbinomial(0.5), wt ~ rnorm(mu,sd),
        envir = list(mu = 50, sd = 20))

Add random variates to a data frame.

Description

Add random variates to a data frame.

Usage

mutate_random(data, input, ...)

## S4 method for signature 'data.frame,formula'
mutate_random(data, input, ...)

## S4 method for signature 'data.frame,character'
mutate_random(data, input, envir = parent.frame(), ...)

## S4 method for signature 'data.frame,list'
mutate_random(data, input, ...)

## S4 method for signature 'data.frame,covset'
mutate_random(data, input, ...)

## S4 method for signature 'data.frame,covobj'
mutate_random(data, input, envir = parent.frame(), ...)

Arguments

Examples

data <- data.frame(ID=1:10, GROUP = sample(c(1,2,3),10,replace=TRUE))

mutate_random(data, AGE[40,90] ~ rnorm(55,50))
mutate_random(data, RE ~ rbeta(1,1) | GROUP)

e <- list(lower=40,upper=140,mu=100,sd=100)

egfr <- covset(EGFR[lower,upper] ~ rnorm(mu,sd))

mutate_random(data,egfr,envir=e)

Simulate from binomial distribution.

Description

Wrapper for rbinom with trial size of 1.

Usage

rbinomial(n, p, ...)

rbern(n, p, ...)

Arguments

Details

The size of each trial is always 1.

Simulate from multivariate normal distribution.

Description

Simulate from multivariate normal distribution.

Usage

rmvnorm(n, mu, Sigma)

rlmvnorm(n, ...)

rmassnorm(n, ...)

rlmassnorm(n, ...)

Arguments

Details

rlmvnorm is a multivariate log normal.

rmassnorm and rlmassnorm simulate the multivariate normal using the MASS package.

Value

Returns a matrix of variates with number of rows equal to n and mumber of columns equal to length of mu.