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stats/sample

src/stats/sample.tur
defn

bootstrap

(bootstrap [col : int stat-fn : int n-reps : int conf-level : float method : int rng : int] :)

one-sample bootstrap confidence interval.

col:int float64 column
stat-fn:int function handle (fn [col :int] :float)
n-reps:int number of bootstrap replicates
conf-level:float confidence level, e.g. 0.95
method:int 0 = percentile, 1 = BCa
rng:int rng handle from stats/rng

:int test-result with estimate = observed stat, ci-low/ci-high set.

Since: ST8

defn

bootstrap-2samp

(bootstrap-2samp [a : int b : int stat-fn : int n-reps : int conf-level : float method : int rng : int] :)

two-sample bootstrap CI on the difference of a statistic.

a:int float64 column
b:int float64 column
stat-fn:int tag (0=mean-diff, 1=sd-ratio)
n-reps:int number of replicates
conf-level:float
method:int 0=percentile, 1=BCa (BCa uses jackknife approx)
rng:int rng handle

:int test-result

Since: ST8

defn

permutation-test

(permutation-test [a : int b : int stat-fn : int n-reps : int alt-tag : int rng : int] :)

non-parametric permutation test.

a:int float64 column (group 1)
b:int float64 column (group 2)
stat-fn:int tag (0=mean-diff, 1=abs-mean-diff)
n-reps:int number of permutations
alt-tag:int 0=two.sided, 1=less, 2=greater
rng:int rng handle

:int test-result with statistic=observed, p-value=permutation p

Since: ST8

defn

train-test-split

(train-test-split [f : int test-frac : float stratify-col : int rng : int] :)

split a frame into train/test subsets.

f:int frame handle
test-frac:float fraction of rows in the test set (e.g. 0.2)
stratify-col:int column handle to stratify on, or 0 for none
rng:int rng handle

:int result<(cons train-frame test-frame)>

Since: ST8

defn

cv-folds

(cv-folds [n : int k : int shuffle? : int rng : int] :)

K-fold cross-validation index sets.

n:int total number of observations
k:int number of folds
shuffle?:int 1 to shuffle indices before splitting
rng:int rng handle (ignored if shuffle?=0)

:int cons list of (cons train-indices test-indices) pairs. Each element is a cons cell; car = cons list of train row indices, cdr = cons list of test row indices.

Since: ST8

defn

cv-folds-stratified

(cv-folds-stratified [col : int k : int shuffle? : int rng : int] :)

stratified K-fold CV.

col:int float64 or int column of class labels
k:int number of folds
shuffle?:int 1 to shuffle within each stratum before assigning
rng:int rng handle

:int same structure as cv-folds.

Since: ST8