Nothing
context("CI of PAF using one to one method")
test_that("Checking paf.confidence.one2one",{
#Expect error when confidence levels are incorrectly specified
expect_error({
set.seed(347618)
X <- as.data.frame(rnorm(100,3,1))
thetahat <- 1.4
thetalow <- 1.2
thetaup <- 1.65
rr <- function(X,theta){exp(X*theta)}
paf.confidence.one2one(X=X, thetahat = thetahat, rr=rr, thetalow = thetalow,
thetaup = thetaup, method = "empirical", confidence = -1)
})
#Expect error when thetaup isn't specified
expect_error({
set.seed(347618)
X <- as.data.frame(rnorm(100,3,1))
thetahat <- 1.4
thetalow <- 1.12
rr <- function(X,theta){exp(X*theta)}
paf.confidence.one2one(X=X, thetahat = thetahat, rr=rr, thetalow = thetalow,
method = "empirical")
})
#Expect error when thetalow isn't specified
expect_error({
set.seed(347618)
X <- as.data.frame(rnorm(100,3,1))
thetahat <- 1.4
thetaup <- 2.3
rr <- function(X,theta){exp(X*theta)}
paf.confidence.one2one(X=X, thetahat = thetahat, rr=rr,
thetaup = thetaup, method = "empirical")
})
#Expect error when dimensions of thetahat, thetaup, and thetalow are different
expect_error({
set.seed(347618)
X <- as.data.frame(rnorm(100,3,1))
thetahat <- 1.4
thetalow <- c(1.3, 1)
thetaup <- 2.1
rr <- function(X,theta){exp(X*theta)}
paf.confidence.one2one(X=X, thetahat = thetahat, rr=rr, thetalow = thetalow,
thetaup = thetaup, method = "empirical")
})
expect_error({
set.seed(347618)
X <- as.data.frame(rnorm(100,3,1))
thetahat <- c(1.4, 1.3)
thetalow <- c(.01, .04)
thetaup <- 1.5
rr <- function(X,theta){exp(X*theta[1]*theta[2])}
paf.confidence.one2one(X=X, thetahat = thetahat, rr=rr, thetalow = thetalow,
thetaup = thetaup, method = "empirical")
})
#Expect error if thetalow > thetahat or thetaup < thetahat
expect_error({
set.seed(347618)
X <- as.data.frame(rnorm(100,3,1))
thetahat <- c(1.4, 1.3)
thetalow <- c(1.1, 1.2)
thetaup <- c(1.5, 1.2)
rr <- function(X,theta){exp(X*theta[1]*theta[2])}
paf.confidence.one2one(X=X, thetahat = thetahat, rr=rr, thetalow = thetalow,
thetaup = thetaup, method = "empirical")
})
expect_error({
set.seed(347618)
X <- as.data.frame(rnorm(100,3,1))
thetahat <- c(1.4, 1.3)
thetalow <- c(1.1, 1.32)
thetaup <- c(1.5, 1.4)
rr <- function(X,theta){exp(X*theta[1]*theta[2])}
paf.confidence.one2one(X=X, thetahat = thetahat, rr=rr, thetalow = thetalow,
thetaup = thetaup, method = "empirical")
})
#Error using approximate method and no value for Xvar
expect_error({
Xmean <- (2.3)
thetahat <- c(1.4, 1.3)
thetalow <- c(1.1, 1.23)
thetaup <- c(1.5, 1.4)
rr <- function(X,theta){exp(X*theta[1]*theta[2])}
paf.confidence.one2one(X=Xmean, thetahat = thetahat, rr=rr, thetalow = thetalow,
thetaup = thetaup, method = "approximate")
})
#Expect equal to zero when exposure is zero and variance of exposure is zero
expect_equal({
Xmean <- as.data.frame(rep(0, 100))
thetahat <- c(1.4, 1.3)
thetalow <- c(1.1, 1.23)
thetaup <- c(1.5, 1.4)
rr <- function(X,theta){exp(X*theta[1]*theta[2])}
paf.confidence.one2one(X=Xmean, thetahat = thetahat, rr=rr, thetalow = thetalow,
thetaup = thetaup, method = "empirical")
}, c("Lower_CI" = 0, "Point_Estimate" = 0, "Upper_CI" = 0))
expect_equal({
Xmean <- as.data.frame(0)
Xvar <- 0
thetahat <- c(1.4, 1.3)
thetalow <- c(1.1, 1.23)
thetaup <- c(1.5, 1.4)
rr <- function(X,theta){exp(X*theta[1]*theta[2])}
paf.confidence.one2one(X=Xmean, thetahat = thetahat, rr=rr, thetalow = thetalow,
thetaup = thetaup, method = "approximate", Xvar=Xvar)
},
c("Lower_CI" = 0, "Point_Estimate" = 0, "Upper_CI" = 0))
})
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