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Assert probability matrix or vector

assert_prob.Rd

Validates that the input is a proper probability matrix or vector representing either a survival function, cumulative distribution function (CDF), cumulative incidence function (CIF), discrete hazard, or discrete density.

Usage

assert_prob(x, times = NULL, type = "surv")

Arguments

x

(numeric() | matrix())
Survival vector or matrix (rows = observations, columns = time points).

times

(numeric() | NULL)
Original time points. If NULL, extracted from names/colnames.

type

(character(1))
Type of probability function: "surv" (default), "cdf", "cif", "haz", or "dens".

Value

Invisibly returns the validated numeric time points.

Details

The following conditions must hold:

  1. The input x is a numeric matrix with no missing values.

  2. Time points (times) are numeric, non-negative, unique, and increasing. If not supplied, they are derived from (col)names(x) (coerced to numeric).

  3. All values are valid probabilities, i.e. lie in \([0,1]\).

  4. Each row is monotone:

    • "surv": non-increasing survival curves, i.e. \(S(t_i) \ge S(t_{i+1})\).

    • "cdf" / "cif": non-decreasing functions, i.e. \(F(t_i) \le F(t_{i+1})\).

    • "haz" / "dens": no monotonicity requirement.

  5. Boundary condition at t = 0:

    • "surv": \(S(0) = 1\).

    • "cdf" / "cif": \(F(0) = 0\).

    • "haz" / "dens": \(t_1 > 0\) (otherwise, nonzero hazard/density at t = 0 implies \(S(0) \neq 1\))

Examples

x = matrix(data = c(1, 0.6, 0.4,
                    0.8, 0.8, 0.7),
           nrow = 2, ncol = 3, byrow = TRUE)

# Explicitly provide time points
assert_prob(x, times = c(12, 34, 42), type = "surv")

# Or use column names as time points
colnames(x) = c(12, 34, 42)
assert_prob(x)

# check CDF
assert_prob(1 - x, type = "cdf")

# check discrete hazards
assert_prob(c(0.2, 0.01, 0.3), times = c(1, 2, 3), type = "haz")

# check discrete densities
assert_prob(c(0.2, 0.01, 0.3), times = c(1, 2, 3), type = "dens")