inspect_prob: Validate vectors of probabilities

In ptfonseca/inspector: Validation of Arguments and Objects in User-Defined Functions

Description

inspect_prob checks if an object is a numeric vector of valid probability values. This can be useful to validate inputs, intermediate calculations or outputs in user-defined functions.

Usage

inspect_prob(x, allow_nas = TRUE, warning_nas = TRUE)

Arguments

x	An arbitrary object.
allow_nas	Logical value. If TRUE then NA and NaN values in x are allowed. If FALSE, execution is stopped and an error message is thrown in case there are NA or NaN values in x.
warning_nas	Logical value. If TRUE then the presence of NA or NaN values in x generates a warning message. NA and NaN values pass silently otherwise (if allow_nas is set to TRUE).

Details

inspect_prob conducts a series of tests to check if x is a numeric vector of valid probability values. Namely, inspect_prob checks if:

• x is NULL or empty.

• x is an atomic vector.

• x is numeric.

• x has NA or NaN values.

• The values of x are in the [0, 1] interval.

Value

inspect_prob does not return any output. There are three possible outcomes:

• The call is silent if:

  • x is a numeric vector of valid probability values and there are no NA or NaN values in x.

  • x is a numeric vector of valid probability values, there are some NA or NaN values in x, allow_nas is set to TRUE and warning_nas is set to FALSE.

• An informative warning message is thrown if x is a numeric vector of valid probability values, there are some NA or NaN values in x and both allow_nas and warning_nas are set to TRUE.

• An informative error message is thrown and the execution is stopped if:

  • x is not a numeric vector of valid probability values.

  • x is a numeric vector of valid probability values, there are some NA or NaN values in x and allow_nas is set to FALSE.

See Also

• inspect_par_bernoulli to check if an object is a valid Bernoulli/Binomial proportion.

• inspect_par_multinomial to check if an object is a numeric vector of valid Multinomial proportions.

Examples

# Calls that pass silently:
x1 <- c(0.1, 0.2, 0.3, 0.4, 0.5)
x2 <- c(0.1, 0.2, 0.3, 0.4, 0.5, NA)
inspect_prob(x1)
inspect_prob(x2, warning_nas = FALSE)
inspect_prob(x2, allow_nas = TRUE, warning_nas = FALSE)

# Calls that throw an informative warning message:
y <- c(0.1, 0.2, NA, 0.4, 0.5)
try(inspect_prob(y))
try(inspect_prob(y, allow_nas = TRUE))
try(inspect_prob(y, allow_nas = TRUE, warning_nas = TRUE))

# Calls that throw an informative error message:
z1 <- c(-0.9, 0, 0.1, 0.2, 0.3, 0.4, 0.5)
try(inspect_prob(z1))
z2 <- c(NA, 0, 0.1, 0.2, 0.3, 0.4, 0.5)
try(inspect_prob(z2, allow_nas = FALSE))
mylist <- list(
  NULL, TRUE, factor(.5), matrix(0.5),
  "0.5", list(0.5), NA, NaN, numeric(0), 1.1, -0.5
)
try(inspect_prob(mylist[[1]]))
try(inspect_prob(mylist[[2]]))
try(inspect_prob(mylist[[3]]))
try(inspect_prob(mylist[[4]]))
try(inspect_prob(mylist[[5]]))
try(inspect_prob(mylist[[6]]))
try(inspect_prob(mylist[[7]]))
try(inspect_prob(mylist[[8]]))
try(inspect_prob(mylist[[9]]))
try(inspect_prob(mylist[[10]]))
try(inspect_prob(mylist[[11]]))

ptfonseca/inspector documentation built on June 23, 2021, 8:21 p.m.