Skip to contents

Survival Distributions with piece-wise Constant Hazards (function factories)

Source: R/pch_functions.R
pch_functions.Rd

Densitiy, distribution function, quantiles, random numbers, hazard function, cumulative hazard function and survival function of survival distributions with piece-wise constant hazards (picewise exponential distributions).

Those functions return functions of one parameter that can be evaluated to give the density, distribution function, ... The parameters t and lambda are checked only once and not at every function evaluation.

Usage

dpch_fun(t, lambda)

ppch_fun(t, lambda)

qpch_fun(t, lambda)

rpch_fun(t, lambda, discrete = FALSE)

hpch_fun(t, lambda)

chpch_fun(t, lambda)

spch_fun(t, lambda)

pch_functions(t, lambda, discrete = FALSE)

Arguments

t

vector of left interval borders

lambda

vector of hazards

discrete

round survival times to whole numbers in RNG

Value

dpch_fun gives the density.

ppch_fun gives the distribution function

qpch_fun gives the quantile function.

rpch_fun gives a function to sample from the given distribution.

hpch_fun gives the hazard function.

chpch_fun gives the cumulative hazard function.

spch_fun gives the survival function.

pch_functions gives an object of class "miniPCH"

Functions

  • dpch_fun(): density of survival distributions with piece-wise constant hazards

  • ppch_fun(): distribution function of survival distributions with piece-wise constant hazards

  • qpch_fun(): quantile function of survival distributions with piece-wise constant hazards

  • rpch_fun(): RNG function of survival distributions with piece-wise constant hazards

  • hpch_fun(): hazard function of survival distributions with piece-wise constant hazards

  • chpch_fun(): cumulative hazard function of survival distributions with piece-wise constant hazards

  • spch_fun(): survival function of survival distributions with piece-wise constant hazards

See also

pch

Examples

pch_density <- dpch_fun(c(0, 3), c(2, 0.1))
pch_density(1:10)
#>  [1] 0.2706705665 0.0366312778 0.0002478752 0.0002242868 0.0002029431
#>  [6] 0.0001836305 0.0001661557 0.0001503439 0.0001360368 0.0001230912
pch_distr <- ppch_fun(c(0, 3), c(2, 0.1))
pch_distr(1:10)
#>  [1] 0.8646647 0.9816844 0.9975212 0.9977571 0.9979706 0.9981637 0.9983384
#>  [8] 0.9984966 0.9986396 0.9987691
pch_quant <- qpch_fun(c(0, 3), c(2, 0.1))
pch_quant(seq(0,1, by=0.1))
#>  [1] 0.00000000 0.05268026 0.11157178 0.17833747 0.25541281 0.34657359
#>  [7] 0.45814537 0.60198640 0.80471896 1.15129255        Inf
rpch_fun_cont  <- rpch_fun(c(0, 3), c(2, 0.1))
rpch_fun_discr <- rpch_fun(c(0, 3), c(2, 0.1), discrete=TRUE)
rpch_fun_cont(15)
#>  [1] 0.01586419 0.12780918 0.17893126 0.50594070 0.32602618 0.28296771
#>  [7] 0.61282612 1.48383075 0.09943208 0.12224736 0.56997177 0.34542053
#> [13] 0.51316351 0.53982317 0.05047632
rpch_fun_discr(15)
#>  [1] 1 1 3 2 1 1 1 1 1 1 1 1 1 1 1
pch_haz <- hpch_fun(c(0, 3), c(2, 0.1))
pch_haz(1:10)
#>  [1] 2.0 2.0 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1
pch_cumhaz <- chpch_fun(c(0, 3), c(2, 0.1))
pch_cumhaz(1:10)
#>  [1] 2.0 4.0 6.0 6.1 6.2 6.3 6.4 6.5 6.6 6.7
pch_surv <- spch_fun(c(0, 3), c(2, 0.1))
pch_surv(1:10)
#>  [1] 0.135335283 0.018315639 0.002478752 0.002242868 0.002029431 0.001836305
#>  [7] 0.001661557 0.001503439 0.001360368 0.001230912
my_pch <- pch_functions(c(0, 3), c(2, 0.1))
my_pch$t
#> [1] 0 3
my_pch$r(15)
#>  [1] 0.8720548 0.1599775 0.4220373 0.2045251 0.4534955 0.1062985 1.4759911
#>  [8] 0.3909678 0.3932933 0.1632788 0.2959297 0.2322185 0.0142311 0.3136677
#> [15] 0.2471739
my_pch$ch(1:10)
#>  [1] 2.0 4.0 6.0 6.1 6.2 6.3 6.4 6.5 6.6 6.7