class DSP::Analysis::SimpleRegression

Overview

Estimates an ordinary least squares regression model with one independent variable. y = intercept + slope * x Standard errors for intercept and slope are available as well as ANOVA, r-square and Pearson's r statistics. Observations (x,y pairs) can be added to the model one at a time or they can be provided in a 2-dimensional array. The observations are not stored in memory, so there is no limit to the number of observations that can be added to the model. Usage Notes: When there are fewer than two observations in the model, or when there is no variation in the x values (i.e. all x values are the same) all statistics return NaN. At least two observations with different x coordinates are required to estimate a bivariate regression model. Getters for the statistics always compute values based on the current set of observations -- i.e., you can get statistics, then add more data and get updated statistics without using a new instance. There is no "compute" method that updates all statistics. Each of the getters performs the necessary computations to return the requested statistic. The intercept term may be suppressed by passing false to the SimpleRegression(boolean) constructor. When the hasIntercept property is false, the model is estimated without a constant term and getIntercept() returns 0.

Defined in:

dsp/analysis/simple_regression.cr

Constant Summary

SERIALVERSIONUID = -3004689053607543335_i64

Serializable version identifier

Constructors

Instance Method Summary

Constructor Detail

def self.new(has_intercept : Bool) #

Create a SimpleRegression instance, specifying whether or not to estimate an intercept. Use false to estimate a model with no intercept. When the hasIntercept property is false, the model is estimated without a constant term and getIntercept() returns 0. Params: includeIntercept – whether or not to include an intercept term in the regression model


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def self.new #

Create an empty SimpleRegression instance


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Instance Method Detail

def add_data(x : Float64, y : Float64) #

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def get_intercept(slope : Float64) : Float64 #

Returns the intercept of the estimated regression line, given the slope. Will return NaN if slope is NaN. Params: slope – current slope Returns: the intercept of the regression line


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def get_intercept : Float64 #

Returns the intercept of the estimated regression line, if hasIntercept() is true; otherwise 0. The least squares estimate of the intercept is computed using the normal equations . The intercept is sometimes denoted b0. Preconditions: At least two observations (with at least two different x values) must have been added before invoking this method. If this method is invoked before a model can be estimated, Double,NaN is returned. Returns: the intercept of the regression line if the model includes an intercept; 0 otherwise See Also: SimpleRegression(boolean)


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def get_slope : Float64 #

Returns the slope of the estimated regression line. The least squares estimate of the slope is computed using the normal equations . The slope is sometimes denoted b1. Preconditions: At least two observations (with at least two different x values) must have been added before invoking this method. If this method is invoked before a model can be estimated, Double.NaN is returned. Returns: the slope of the regression line


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