Univariate case…

library(ldamatch)
set.seed(257)

SIZE <- 15
condition <- as.factor(c(rep("control", 2 * SIZE), rep("treatment", SIZE)))
covariate1 <- c(rnorm(2 * SIZE), rnorm(SIZE, 1, 2))

Univariate case (with heuristic search)…

is.in <- ldamatch(condition, covariate1, t_halt)

## Initial group sizes:  control: 30    treatment: 15 
## Starting heuristic search.
## Finished heuristic search in 0.007 seconds.
## Eventual group sizes: control: 28    treatment: 14 
## Removed subjects:     control: 2 treatment: 1

print(table(condition, is.in))

##            is.in
## condition   FALSE TRUE
##   control       2   28
##   treatment     1   14

Univariate case (with Monte Carlo search)…

is.in <- ldamatch(condition, covariate1, t_halt, method = "monte")

## Initial group sizes:  control: 30    treatment: 15 
## Starting montecarlo search.
## Finished montecarlo search in 0.005 seconds.
## Eventual group sizes: control: 30    treatment: 13 
## Removed subjects:     control: 0 treatment: 2

print(table(condition, is.in))

##            is.in
## condition   FALSE TRUE
##   control       0   30
##   treatment     2   13

Multivariate case…

covariate2 <- c(rnorm(2 * SIZE), rnorm(SIZE, 1, 2))
covariates <- cbind(covariate1, covariate2)

Multivariate case (with heuristic search)…

is.in <- ldamatch(condition, covariates, t_halt)

## Initial group sizes:  control: 30    treatment: 15 
## Starting heuristic search.
## Finished heuristic search in 0.028 seconds.
## Eventual group sizes: control: 25    treatment: 13 
## Removed subjects:     control: 5 treatment: 2

print(table(condition, is.in))

##            is.in
## condition   FALSE TRUE
##   control       5   25
##   treatment     2   13

Multivariate case (with Monte Carlo search)…

is.in <- ldamatch(condition, covariates, t_halt, method = "monte")

## Initial group sizes:  control: 30    treatment: 15 
## Starting montecarlo search.
## Finished montecarlo search in 0.083 seconds.
## Eventual group sizes: control: 29    treatment: 11 
## Removed subjects:     control: 1 treatment: 4

print(table(condition, is.in))

##            is.in
## condition   FALSE TRUE
##   control       1   29
##   treatment     4   11

Multivariate case (with special proportions and Wilcox test)…

my.props <- prop.table(c(control = 4, treatment = 3))
is.in <- ldamatch(condition, covariates, U_halt, props = my.props)

## Initial group sizes:  control: 30    treatment: 15 
## Starting heuristic search.
## Finished heuristic search in 0.045 seconds.
## Eventual group sizes: control: 20    treatment: 15 
## Removed subjects:     control: 10    treatment: 0

print(table(condition, is.in))

##            is.in
## condition   FALSE TRUE
##   control      10   20
##   treatment     0   15

Multivariate case (with Wilks test)…

is.in <- ldamatch(condition, covariates, wilks_halt)

## Initial group sizes:  control: 30    treatment: 15 
## Starting heuristic search.
## Finished heuristic search in 0.036 seconds.
## Eventual group sizes: control: 25    treatment: 12 
## Removed subjects:     control: 5 treatment: 3

print(table(condition, is.in))

##            is.in
## condition   FALSE TRUE
##   control       5   25
##   treatment     3   12

Multivariate case (with Wilks test and Monte Carlo search)…

is.in <- ldamatch(condition, covariates, wilks_halt, method = "monte")

## Initial group sizes:  control: 30    treatment: 15 
## Starting montecarlo search.
## Finished montecarlo search in 0.117 seconds.
## Eventual group sizes: control: 27    treatment: 10 
## Removed subjects:     control: 3 treatment: 5

print(table(condition, is.in))

##            is.in
## condition   FALSE TRUE
##   control       3   27
##   treatment     5   10

Multivariate case (with Anderson-Darling test and heuristic search)…

is.in <- ldamatch(condition, covariates, ad_halt, method = "heuristic")

## Initial group sizes:  control: 30    treatment: 15 
## Starting heuristic search.
## Finished heuristic search in 0.681 seconds.
## Eventual group sizes: control: 25    treatment: 12 
## Removed subjects:     control: 5 treatment: 3

print(table(condition, is.in))

##            is.in
## condition   FALSE TRUE
##   control       5   25
##   treatment     3   12

Multivariate case (with t-test and Anderson-Darling test simultaneously)…

combined_halting_test <- create_halting_test(c(t_halt, ad_halt))
threshes <- c(.2, .02)
is.in <- ldamatch(condition, covariates, combined_halting_test, threshes)

## Initial group sizes:  control: 30    treatment: 15 
## Starting heuristic search.
## Finished heuristic search in 0.129 seconds.
## Eventual group sizes: control: 25    treatment: 13 
## Removed subjects:     control: 5 treatment: 2

print(table(condition, is.in))

##            is.in
## condition   FALSE TRUE
##   control       5   25
##   treatment     2   13

Univariate case (with exhaustive search)…

estimate_exhaustive(min_preserved = 42, condition, cases_per_second = 100)

## If 44 of 45 kept: at most 45 cases. If 100 cases per second evaluated: 0.45 seconds.
## If 43 of 45 kept: at most 1035 cases. If 100 cases per second evaluated: 10.35 seconds.
## If 42 of 45 kept: at most 15225 cases. If 100 cases per second evaluated: 2.538 minutes.

## [1] 15225

foreach::registerDoSEQ()
is.ins <- ldamatch(condition, covariate1, t_halt, method = "exhaustive")

## Initial group sizes:  control: 30    treatment: 15 
## Starting exhaustive search.
## Created 2 group size configurations each with a total size of 44 
## control: 29 treatment: 15 KL_diverg: 0.000128651338541343 
## Size of Cartesian product: 30 
## Number of cases processed per second: 163.0435 
## control: 30 treatment: 14 KL_diverg: 0.000520578560755861 
## Size of Cartesian product: 15 
## Number of cases processed per second: 300 
## Created 3 group size configurations each with a total size of 43 
## control: 29 treatment: 14 KL_diverg: 0.000135741532290407 
## Size of Cartesian product: 450 
## Number of cases processed per second: 387.931 
## control: 28 treatment: 15 KL_diverg: 0.000536783341068091 
## Size of Cartesian product: 435 
## Number of cases processed per second: 327.8071 
## control: 30 treatment: 13 KL_diverg: 0.0021993283249259 
## Size of Cartesian product: 105 
## Number of cases processed per second: 411.7647 
## Finished exhaustive search in 3.033 seconds.
## Eventual group sizes: control: 30    treatment: 13 
## Removed subjects:     control: 0 treatment: 2

print(table(condition, is.ins[[1]]))

##            
## condition   FALSE TRUE
##   control       0   30
##   treatment     2   13

print(length(is.ins))

## [1] 1

# (Confirm exhaustive search by applying heuristic search to it.)
is.in <- ldamatch(condition[is.ins[[1]]], covariate1[is.ins[[1]]], t_halt)
print(table(condition[is.ins[[1]]], is.in))

##            is.in
##             TRUE
##   control     30
##   treatment   13