@addmaple/stats API Reference

@addmaple/stats API Reference - v0.2.4

Table of contents

Classes

• RegressionWorkspace

Interfaces

• DistributionHandle
• NormalParams
• GammaParams
• BetaParams
• StudentTParams
• ChiSquaredParams
• FisherFParams
• ExponentialParams
• PoissonParams
• BinomialParams
• UniformParams
• CauchyParams
• LaplaceParams
• LogNormalParams
• WeibullParams
• ParetoParams
• TriangularParams
• InverseGammaParams
• NegativeBinomialParams
• ArrayResult
• HistogramWithEdgesResult
• TestResult
• RegressionCoeffs
• RegressionCoeffsF32
• RegressionResult
• DescriptiveStatsResult
• WasmRegressionResult
• QuartilesResult
• AnovaResult
• ChiSquareResult
• TukeyPairResult
• TukeyHsdResult
• StatsWasmModule
• DistributionsWasmModule
• QuantilesWasmModule
• CorrelationWasmModule
• TestsWasmModule
• FullWasmModule

Variables

• BinningPresets
• WASM_NOT_INITIALIZED_ERROR

Functions

• covariance
• corrcoeff
• spearmancoeff
• descriptiveStats
• getDistributionsWasm
• setDistributionsWasm
• normal
• gamma
• beta
• studentT
• chiSquared
• fisherF
• exponential
• poisson
• binomial
• uniform
• cauchy
• laplace
• logNormal
• weibull
• pareto
• triangular
• inverseGamma
• negativeBinomial
• init
• percentile
• percentileInclusive
• percentileExclusive
• percentileOfScore
• qscore
• qtest
• quartiles
• iqr
• percentiles
• quantiles
• weightedPercentile
• weightedQuantiles
• weightedMedian
• histogramEdges
• histogramBinning
• f64View
• f32View
• copyToWasmMemory
• copyToWasmMemoryF32
• readWasmArray
• runUnaryArrayOp
• loadWasmModule
• sum
• mean
• variance
• sampleVariance
• stdev
• sampleStdev
• min
• max
• product
• range
• median
• mode
• geomean
• skewness
• kurtosis
• stanMoment
• coeffvar
• meandev
• meddev
• pooledvariance
• pooledstdev
• cumsum
• cumprod
• diff
• rank
• deviation
• histogram
• cumreduce
• ttest
• ztest
• normalci
• tci
• regress
• regressNaive
• regressSimd
• regressWasmKernels
• anovaFScore
• anovaTest
• chiSquareTest
• anovaFScoreCategorical
• anovaTestCategorical
• tukeyHsdCategorical

Variables

BinningPresets

• Const BinningPresets: Object

Presets for common histogram binning strategies.

Type declaration

Name	Type
autoFD	(bins?: number) => HistogramBinningOptions
autoScott	(bins?: number) => HistogramBinningOptions
autoSqrt	(bins?: number) => HistogramBinningOptions
autoWithTailCollapse	(k: number, bins?: number) => HistogramBinningOptions
equalFrequency	(bins: number) => HistogramBinningOptions
fixedWidth	(bins: number) => HistogramBinningOptions
deciles	() => HistogramBinningOptions
quartiles	() => HistogramBinningOptions
custom	(edges: Float64Array | number[]) => HistogramBinningOptions

Defined in

quantiles.ts:394

---

WASM_NOT_INITIALIZED_ERROR

• Const WASM_NOT_INITIALIZED_ERROR: "Wasm module not initialized. Call init() first."

The consistent error message for uninitialized WASM modules.

Defined in

shared.ts:149

Functions

covariance

▸ covariance(x, y): number

Calculate the covariance between two arrays.

Parameters

Name	Type
x	ArrayLike<number>
y	ArrayLike<number>

Returns

number

Defined in

correlation.ts:66

---

corrcoeff

▸ corrcoeff(x, y): number

Calculate the Pearson correlation coefficient.

Parameters

Name	Type
x	ArrayLike<number>
y	ArrayLike<number>

Returns

number

Defined in

correlation.ts:73

---

spearmancoeff

▸ spearmancoeff(x, y): number

Calculate the Spearman rank correlation coefficient.

Parameters

Name	Type
x	ArrayLike<number>
y	ArrayLike<number>

Returns

number

Defined in

correlation.ts:80

---

descriptiveStats

▸ descriptiveStats(data): DescriptiveStatsResult

Calculate a rich set of descriptive statistics for an array in one call.

This helper wraps core vector statistics (mean, variance, quartiles, skewness, etc.) and returns them in a single object.

Parameters

Name	Type	Description
data	ArrayLike<number>	Input array of numbers

Returns

DescriptiveStatsResult

An object with common descriptive statistics

Defined in

descriptive.ts:14

---

getDistributionsWasm

▸ getDistributionsWasm(): DistributionsWasmModule | null

Get the current WASM module instance.

Returns

DistributionsWasmModule | null

Defined in

distributions.ts:14

---

setDistributionsWasm

▸ setDistributionsWasm(mod): void

Set the WASM module instance.

Parameters

Name	Type
mod	DistributionsWasmModule

Returns

void

Defined in

distributions.ts:21

---

normal

▸ normal(params?): DistributionHandle

Parameters

Name	Type
params	NormalParams

Returns

DistributionHandle

Defined in

distributions.ts:76

---

gamma

▸ gamma(params?): DistributionHandle

Parameters

Name	Type
params	GammaParams

Returns

DistributionHandle

Defined in

distributions.ts:95

---

beta

▸ beta(params?): DistributionHandle

Parameters

Name	Type
params	BetaParams

Returns

DistributionHandle

Defined in

distributions.ts:113

---

studentT

▸ studentT(params?): DistributionHandle

Parameters

Name	Type
params	StudentTParams

Returns

DistributionHandle

Defined in

distributions.ts:132

---

chiSquared

▸ chiSquared(params?): DistributionHandle

Parameters

Name	Type
params	ChiSquaredParams

Returns

DistributionHandle

Defined in

distributions.ts:150

---

fisherF

▸ fisherF(params?): DistributionHandle

Parameters

Name	Type
params	FisherFParams

Returns

DistributionHandle

Defined in

distributions.ts:167

---

exponential

▸ exponential(params?): DistributionHandle

Parameters

Name	Type
params	ExponentialParams

Returns

DistributionHandle

Defined in

distributions.ts:185

---

poisson

▸ poisson(params?): DistributionHandle

Parameters

Name	Type
params	PoissonParams

Returns

DistributionHandle

Defined in

distributions.ts:201

---

binomial

▸ binomial(params?): DistributionHandle

Parameters

Name	Type
params	BinomialParams

Returns

DistributionHandle

Defined in

distributions.ts:218

---

uniform

▸ uniform(params?): DistributionHandle

Parameters

Name	Type
params	UniformParams

Returns

DistributionHandle

Defined in

distributions.ts:236

---

cauchy

▸ cauchy(params?): DistributionHandle

Parameters

Name	Type
params	CauchyParams

Returns

DistributionHandle

Defined in

distributions.ts:254

---

laplace

▸ laplace(params?): DistributionHandle

Parameters

Name	Type
params	LaplaceParams

Returns

DistributionHandle

Defined in

distributions.ts:272

---

logNormal

▸ logNormal(params?): DistributionHandle

Parameters

Name	Type
params	LogNormalParams

Returns

DistributionHandle

Defined in

distributions.ts:290

---

weibull

▸ weibull(params?): DistributionHandle

Parameters

Name	Type
params	WeibullParams

Returns

DistributionHandle

Defined in

distributions.ts:308

---

pareto

▸ pareto(params?): DistributionHandle

Parameters

Name	Type
params	ParetoParams

Returns

DistributionHandle

Defined in

distributions.ts:326

---

triangular

▸ triangular(params?): DistributionHandle

Parameters

Name	Type
params	TriangularParams

Returns

DistributionHandle

Defined in

distributions.ts:345

---

inverseGamma

▸ inverseGamma(params?): DistributionHandle

Parameters

Name	Type
params	InverseGammaParams

Returns

DistributionHandle

Defined in

distributions.ts:364

---

negativeBinomial

▸ negativeBinomial(params?): DistributionHandle

Parameters

Name	Type
params	NegativeBinomialParams

Returns

DistributionHandle

Defined in

distributions.ts:382

---

init

▸ init(options?): Promise<void>

Initialize the full wasm module (SIMD-aware).

This function must be called once before using any statistics functions. It's safe to call multiple times - it will only initialize once.

Parameters

Name	Type	Description
options	Object	Initialization options
options.inline?	boolean	If true, use the inline (base64) version of the WASM module.

Returns

Promise<void>

Defined in

index.ts:54

---

percentile

▸ percentile(data, k, exclusive?): number

Calculate a percentile of an array.

Parameters

Name	Type	Default value	Description
data	ArrayLike<number>	undefined	Sorted or unsorted array
k	number	undefined	Percentile (0 to 1)
exclusive	boolean	false	If true, use exclusive percentile calculation

Returns

number

Defined in

quantiles.ts:58

---

percentileInclusive

▸ percentileInclusive(data, k): number

Parameters

Name	Type
data	ArrayLike<number>
k	number

Returns

number

Defined in

quantiles.ts:72

---

percentileExclusive

▸ percentileExclusive(data, k): number

Parameters

Name	Type
data	ArrayLike<number>
k	number

Returns

number

Defined in

quantiles.ts:86

---

percentileOfScore

▸ percentileOfScore(data, score, strict?): number

Calculate the percentile rank of a score.

Parameters

Name	Type	Default value
data	ArrayLike<number>	undefined
score	number	undefined
strict	boolean	false

Returns

number

Defined in

quantiles.ts:103

---

qscore

▸ qscore(data, score, strict?): number

Calculate the Q-score (quantile score) of a value.

Parameters

Name	Type	Default value
data	ArrayLike<number>	undefined
score	number	undefined
strict	boolean	false

Returns

number

Defined in

quantiles.ts:120

---

qtest

▸ qtest(data, score, qLower, qUpper): boolean

Perform a quantile test.

Parameters

Name	Type
data	ArrayLike<number>
score	number
qLower	number
qUpper	number

Returns

boolean

Defined in

quantiles.ts:127

---

quartiles

▸ quartiles(data): [number, number, number]

Calculate quartiles (Q1, Q2, Q3).

Parameters

Name	Type
data	ArrayLike<number>

Returns

[number, number, number]

Defined in

quantiles.ts:144

---

iqr

▸ iqr(data): number

Calculate interquartile range (IQR).

Parameters

Name	Type
data	ArrayLike<number>

Returns

number

Defined in

quantiles.ts:161

---

percentiles

▸ percentiles(data, ps): Float64Array

Calculate multiple percentiles at once.

Parameters

Name	Type
data	ArrayLike<number>
ps	ArrayLike<number>

Returns

Float64Array

Defined in

quantiles.ts:178

---

quantiles

▸ quantiles(data, qs): Float64Array

Calculate multiple quantiles at once.

Parameters

Name	Type
data	ArrayLike<number>
qs	ArrayLike<number>

Returns

Float64Array

Defined in

quantiles.ts:185

---

weightedPercentile

▸ weightedPercentile(data, weights, p): number

Calculate a weighted percentile.

Parameters

Name	Type
data	ArrayLike<number>
weights	ArrayLike<number>
p	number

Returns

number

Defined in

quantiles.ts:211

---

weightedQuantiles

▸ weightedQuantiles(data, weights, qs): Float64Array

Calculate multiple weighted quantiles at once.

Parameters

Name	Type
data	ArrayLike<number>
weights	ArrayLike<number>
qs	ArrayLike<number>

Returns

Float64Array

Defined in

quantiles.ts:233

---

weightedMedian

▸ weightedMedian(data, weights): number

Calculate the weighted median.

Parameters

Name	Type
data	ArrayLike<number>
weights	ArrayLike<number>

Returns

number

Defined in

quantiles.ts:263

---

histogramEdges

▸ histogramEdges(data, edges): Float64Array

Calculate a histogram with specified bin edges.

Parameters

Name	Type
data	ArrayLike<number>
edges	ArrayLike<number>

Returns

Float64Array

Defined in

quantiles.ts:304

---

histogramBinning

▸ histogramBinning(data, options): HistogramBinningResult

Advanced histogram binning function.

Parameters

Name	Type
data	ArrayLike<number>
options	number | HistogramBinningOptions

Returns

HistogramBinningResult

Defined in

quantiles.ts:341

---

f64View

▸ f64View(ptr, len, memory): Float64Array

Create a Float64Array view into WASM memory.

Parameters

Name	Type
ptr	number
len	number
memory	Memory

Returns

Float64Array

Defined in

shared.ts:9

---

f32View

▸ f32View(ptr, len, memory): Float32Array

Create a Float32Array view into WASM memory.

Parameters

Name	Type
ptr	number
len	number
memory	Memory

Returns

Float32Array

Defined in

shared.ts:16

---

copyToWasmMemory

▸ copyToWasmMemory(data, view): void

Efficiently copy data to WASM memory.

Performance note: Float64Array and plain Array<number> are fastest. Other array-likes may use a fallback loop which is slower.

Parameters

Name	Type
data	ArrayLike<number>
view	Float64Array

Returns

void

Defined in

shared.ts:26

---

copyToWasmMemoryF32

▸ copyToWasmMemoryF32(data, view): void

Efficiently copy data to WASM memory (f32).

Parameters

Name	Type
data	ArrayLike<number>
view	Float32Array

Returns

void

Defined in

shared.ts:52

---

readWasmArray

▸ readWasmArray(result, memory): Float64Array

Read an array from WASM memory and return a copy.

Parameters

Name	Type
result	ArrayResult
memory	Memory

Returns

Float64Array

Defined in

shared.ts:72

---

runUnaryArrayOp

▸ runUnaryArrayOp(data, kernel, wasm, memory): Float64Array

Run a unary array operation using a WASM kernel.

Parameters

Name	Type
data	ArrayLike<number>
kernel	ArrayKernel
wasm	BaseWasmModule
memory	Memory

Returns

Float64Array

Defined in

shared.ts:96

---

loadWasmModule

▸ loadWasmModule(moduleDir, inline?): Promise<any>

Load a WASM module using wasm-bindgen-lite loaders.

Parameters

Name	Type	Default value
moduleDir	string	undefined
inline	boolean	false

Returns

Promise<any>

Defined in

shared.ts:124

---

sum

▸ sum(data): number

Calculate the sum of an array.

Parameters

Name	Type	Description
data	ArrayLike<number>	Array of numbers to sum

Returns

number

The sum of all elements

Defined in

stats.ts:78

---

mean

▸ mean(data): number

Calculate the arithmetic mean (average) of an array.

Parameters

Name	Type	Description
data	ArrayLike<number>	Array of numbers

Returns

number

The mean value, or NaN if array is empty

Defined in

stats.ts:88

---

variance

▸ variance(data): number

Calculate the population variance of an array.

Parameters

Name	Type
data	ArrayLike<number>

Returns

number

Defined in

stats.ts:95

---

sampleVariance

▸ sampleVariance(data): number

Calculate the sample variance of an array (Bessel's correction).

Parameters

Name	Type
data	ArrayLike<number>

Returns

number

Defined in

stats.ts:102

---

stdev

▸ stdev(data): number

Calculate the standard deviation (population) of an array.

Parameters

Name	Type
data	ArrayLike<number>

Returns

number

Defined in

stats.ts:111

---

sampleStdev

▸ sampleStdev(data): number

Calculate the sample standard deviation of an array.

Parameters

Name	Type
data	ArrayLike<number>

Returns

number

Defined in

stats.ts:118

---

min

▸ min(data): number

Calculate the minimum value in an array.

Parameters

Name	Type
data	ArrayLike<number>

Returns

number

Defined in

stats.ts:127

---

max

▸ max(data): number

Calculate the maximum value in an array.

Parameters

Name	Type
data	ArrayLike<number>

Returns

number

Defined in

stats.ts:134

---

product

▸ product(data): number

Calculate the product of all elements in an array.

Parameters

Name	Type
data	ArrayLike<number>

Returns

number

Defined in

stats.ts:141

---

range

▸ range(data): number

Calculate the range (max - min) of an array.

Parameters

Name	Type
data	ArrayLike<number>

Returns

number

Defined in

stats.ts:148

---

median

▸ median(data): number

Calculate the median of an array.

Parameters

Name	Type
data	ArrayLike<number>

Returns

number

Defined in

stats.ts:155

---

mode

▸ mode(data): number

Calculate the mode of an array.

Parameters

Name	Type
data	ArrayLike<number>

Returns

number

Defined in

stats.ts:162

---

geomean

▸ geomean(data): number

Calculate the geometric mean of an array.

Parameters

Name	Type
data	ArrayLike<number>

Returns

number

Defined in

stats.ts:169

---

skewness

▸ skewness(data): number

Calculate the skewness of an array.

Parameters

Name	Type
data	ArrayLike<number>

Returns

number

Defined in

stats.ts:176

---

kurtosis

▸ kurtosis(data): number

Calculate the kurtosis of an array.

Parameters

Name	Type
data	ArrayLike<number>

Returns

number

Defined in

stats.ts:183

---

stanMoment

▸ stanMoment(data, k): number

Calculate the k-th standardized moment.

Parameters

Name	Type
data	ArrayLike<number>
k	number

Returns

number

Defined in

stats.ts:190

---

coeffvar

▸ coeffvar(data): number

Calculate the coefficient of variation.

Parameters

Name	Type
data	ArrayLike<number>

Returns

number

Defined in

stats.ts:197

---

meandev

▸ meandev(data): number

Calculate the mean absolute deviation.

Parameters

Name	Type
data	ArrayLike<number>

Returns

number

Defined in

stats.ts:204

---

meddev

▸ meddev(data): number

Calculate the median absolute deviation.

Parameters

Name	Type
data	ArrayLike<number>

Returns

number

Defined in

stats.ts:211

---

pooledvariance

▸ pooledvariance(data1, data2): number

Calculate the pooled variance of two arrays.

Parameters

Name	Type
data1	ArrayLike<number>
data2	ArrayLike<number>

Returns

number

Defined in

stats.ts:218

---

pooledstdev

▸ pooledstdev(data1, data2): number

Calculate the pooled standard deviation of two arrays.

Parameters

Name	Type
data1	ArrayLike<number>
data2	ArrayLike<number>

Returns

number

Defined in

stats.ts:240

---

cumsum

▸ cumsum(data): Float64Array

Calculate the cumulative sum.

Parameters

Name	Type
data	ArrayLike<number>

Returns

Float64Array

Defined in

stats.ts:262

---

cumprod

▸ cumprod(data): Float64Array

Calculate the cumulative product.

Parameters

Name	Type
data	ArrayLike<number>

Returns

Float64Array

Defined in

stats.ts:279

---

diff

▸ diff(data): Float64Array

Calculate the difference between consecutive elements.

Parameters

Name	Type
data	ArrayLike<number>

Returns

Float64Array

Defined in

stats.ts:296

---

rank

▸ rank(data): Float64Array

Calculate the rank of each element.

Parameters

Name	Type
data	ArrayLike<number>

Returns

Float64Array

Defined in

stats.ts:313

---

deviation

▸ deviation(data): Float64Array

Calculate the deviation from the mean for each element.

Parameters

Name	Type
data	ArrayLike<number>

Returns

Float64Array

Defined in

stats.ts:330

---

histogram

▸ histogram(data, binCount?): Float64Array

Calculate a histogram with specified number of bins.

Parameters

Name	Type	Default value
data	ArrayLike<number>	undefined
binCount	number	4

Returns

Float64Array

Defined in

stats.ts:347

---

cumreduce

▸ cumreduce(data, initialValue, reducer): Float64Array

Cumulative reduction using a custom reducer function.

Note: This is implemented in JS to allow custom reducers.

Parameters

Name	Type
data	ArrayLike<number>
initialValue	number
reducer	(acc: number, val: number) => number

Returns

Float64Array

Defined in

stats.ts:366

---

ttest

▸ ttest(data, mu0): TestResult

Perform a one-sample t-test.

Parameters

Name	Type
data	ArrayLike<number>
mu0	number

Returns

TestResult

Defined in

tests.ts:54

---

ztest

▸ ztest(data, mu0, sigma): TestResult

Perform a one-sample Z-test.

Parameters

Name	Type
data	ArrayLike<number>
mu0	number
sigma	number

Returns

TestResult

Defined in

tests.ts:75

---

normalci

▸ normalci(alpha, mean, se): number[]

Calculate a confidence interval for a normal distribution.

Parameters

Name	Type
alpha	number
mean	number
se	number

Returns

number[]

Defined in

tests.ts:96

---

tci

▸ tci(alpha, mean, stdev, n): number[]

Calculate a confidence interval for a Student's t-distribution.

Parameters

Name	Type
alpha	number
mean	number
stdev	number
n	number

Returns

number[]

Defined in

tests.ts:105

---

regress

▸ regress(x, y): RegressionResult

Perform simple linear regression.

Parameters

Name	Type
x	ArrayLike<number>
y	ArrayLike<number>

Returns

RegressionResult

Defined in

tests.ts:114

---

regressNaive

▸ regressNaive(x, y): RegressionResult

Perform regression using the naive implementation.

Parameters

Name	Type
x	ArrayLike<number>
y	ArrayLike<number>

Returns

RegressionResult

Defined in

tests.ts:149

---

regressSimd

▸ regressSimd(x, y): RegressionResult

Perform regression using the SIMD implementation.

Parameters

Name	Type
x	ArrayLike<number>
y	ArrayLike<number>

Returns

RegressionResult

Defined in

tests.ts:172

---

regressWasmKernels

▸ regressWasmKernels(x, y): RegressionResult

Perform regression using WASM kernels.

Parameters

Name	Type
x	ArrayLike<number>
y	ArrayLike<number>

Returns

RegressionResult

Defined in

tests.ts:195

---

anovaFScore

▸ anovaFScore(groups): number

Perform one-way ANOVA and return the F-score.

Parameters

Name	Type
groups	ArrayLike<number>[]

Returns

number

Defined in

tests.ts:298

---

anovaTest

▸ anovaTest(groups): AnovaResult

Perform one-way ANOVA and return full results.

Parameters

Name	Type
groups	ArrayLike<number>[]

Returns

AnovaResult

Defined in

tests.ts:331

---

chiSquareTest

▸ chiSquareTest(cat1, cat2, options?): ChiSquareResult

Perform Chi-Square test of independence.

Parameters

Name	Type
cat1	string[]
cat2	string[]
options	Object
options.cardinality1?	number
options.cardinality2?	number

Returns

ChiSquareResult

Defined in

tests.ts:390

---

anovaFScoreCategorical

▸ anovaFScoreCategorical(groups, values): number

Perform ANOVA with categorical labels.

Parameters

Name	Type
groups	string[]
values	number[]

Returns

number

Defined in

tests.ts:426

---

anovaTestCategorical

▸ anovaTestCategorical(groups, values): AnovaResult

Perform full ANOVA test with categorical labels.

Parameters

Name	Type
groups	string[]
values	number[]

Returns

AnovaResult

Defined in

tests.ts:445

---

tukeyHsdCategorical

▸ tukeyHsdCategorical(groups, values): TukeyHsdResult

Perform Tukey HSD test with categorical labels.

Parameters

Name	Type
groups	string[]
values	number[]

Returns

TukeyHsdResult

Defined in

tests.ts:471