dv_stats library
Statistical functions for data analysis.
Classes
- ExponentialRegressionResult
- Result of an exponential regression.
- KernelDensityResult
- Result of kernel density estimation.
- LinearRegressionResult
- Result of a linear regression.
- LoessResult
- Result of LOESS (locally weighted scatterplot smoothing).
- PolynomialRegressionResult
- Result of polynomial regression.
Enums
- KernelType
- Kernel types for density estimation.
Functions
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correlation(
List< double> x, List<double> y) → double - Computes the Pearson correlation coefficient between two series.
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covariance(
List< double> x, List<double> y) → double - Computes the covariance between two series.
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exponentialMovingAverage(
List< double> data, {required double alpha}) → List<double> - Computes the exponential moving average of a series.
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exponentialRegression(
List< double> x, List<double> y) → ExponentialRegressionResult - Computes exponential regression for the given data points.
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kernelDensityEstimation(
List< double> data, {double? bandwidth, KernelType kernel = KernelType.gaussian, int nPoints = 100, List<double> ? range}) → KernelDensityResult - Computes kernel density estimation for a set of data points.
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kurtosis(
List< double> data) → double? - Computes the kurtosis of a distribution.
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linearRegression(
List< double> x, List<double> y) → LinearRegressionResult - Computes simple linear regression for the given data points.
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loess(
List< double> x, List<double> y, {double span = 0.75, int degree = 1}) → LoessResult - Computes LOESS smoothing for the given data.
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movingAverage(
List< double> data, {required int window, bool center = false}) → List<double?> - Computes the simple moving average of a series.
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polynomialRegression(
List< double> x, List<double> y, {required int degree}) → PolynomialRegressionResult - Computes polynomial regression for the given data points.
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skewness(
List< double> data) → double? - Computes the skewness of a distribution.
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spearmanCorrelation(
List< double> x, List<double> y) → double - Computes the Spearman rank correlation coefficient.
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tTest(
List< double> a, List<double> b) → (double, double) - Performs a two-sample t-test.