Linear (FSharp.Stats) | FSharp.Stats

FSharp.Stats

Linear Module

Namespace: FSharp.Stats.Fitting
Assembly: FSharp.Stats.dll
Parent Module: RobustRegression

Simple linear regression using straight lines: f(x) = a + bx.

Functions and values

Function or value	Description
`predict coef x` Full Usage: `predict coef x` Parameters: coef : `Coefficients` - vector of coefficients, sorted as [intercept;slope] x : `float` - x value of which the corresponding y value should be predicted Returns: `float` predicted y value with given coefficients at X=x	Takes vector of [intercept; slope] and x value to predict the corresponding y value Equal to OLS.Linear.Univariable.predict! coef : `Coefficients` vector of coefficients, sorted as [intercept;slope] x : `float` x value of which the corresponding y value should be predicted Returns: `float` predicted y value with given coefficients at X=x Example `// e.g. days since experiment start let xData = vector [\|1. .. 100.\|] // e.g. plant size in cm let yData = vector [\|4.;7.;8.;9.;7.;11.; ...\|] // Estimate the intercept and slope of a line, that fits the data. let coefficients = LinearRegression.RobustRegression.Linear.theilEstimator xData yData // Predict the size on day 10.5 LinearRegression.RobustRegression.Linear.predict coefficients 10.5` val xData: obj val yData: obj
`theilEstimator xData yData` Full Usage: `theilEstimator xData yData` Parameters: xData : `Vector<float>` - vector of x values yData : `Vector<float>` - vector of y values Returns: `Coefficients` vector of polynomial coefficients sorted as [intercept;constant;quadratic;...]	Calculates simple linear regression coefficients using theil's incomplete method in the form of [\|intercept; slope;\|]. Performs well if outlier corrupt the regression line. Not robust if data count is low! http://195.134.76.37/applets/AppletTheil/Appl_Theil2.html xData : `Vector<float>` vector of x values yData : `Vector<float>` vector of y values Returns: `Coefficients` vector of polynomial coefficients sorted as [intercept;constant;quadratic;...] Example `// e.g. days since experiment start let xData = vector [\|1. .. 100.\|] // e.g. plant size in cm let yData = vector [\|4.;7.;8.;9.;7.;11.; ...\|] // Estimate the intercept and slope of a line, that fits the data. let coefficients = LinearRegression.RobustRegression.Linear.theilEstimator xData yData` val xData: obj val yData: obj
`theilSenEstimator xData yData` Full Usage: `theilSenEstimator xData yData` Parameters: xData : `Vector<float>` - vector of x values yData : `Vector<float>` - vector of y values Returns: `Coefficients` vector of polynomial coefficients sorted as [intercept;constant;quadratic;...]	Calculates simple linear regression coefficients using the Theil-Sen estimator in the form of [\|intercept; slope;\|]. Performs well if outlier corrupt the regression line. Not robust if data count is low! xData : `Vector<float>` vector of x values yData : `Vector<float>` vector of y values Returns: `Coefficients` vector of polynomial coefficients sorted as [intercept;constant;quadratic;...] Example `// e.g. days since experiment start let xData = vector [\|1. .. 100.\|] // e.g. plant size in cm let yData = vector [\|4.;7.;8.;9.;7.;11.; ...\|] // Estimate the intercept and slope of a line, that fits the data. let coefficients = LinearRegression.RobustRegression.Linear.theilSenEstimator xData yData` val xData: obj val yData: obj