Numerix v0.4.2 Numerix.LinearRegression
Linear regression functions.
Summary
Functions
Least squares best fit for points {x, y}
to a line y:x↦a+bx
where x
is the predictor and y
the response
Estimates a response y
given a predictor x
and a set of predictors and responses, i.e.
it calculates y
in y:x↦a+bx
Measures how close the observed data are to the fitted regression line, i.e. how accurate the prediction is given the actual data
Functions
Least squares best fit for points {x, y}
to a line y:x↦a+bx
where x
is the predictor and y
the response.
Returns a tuple containing the intercept a
and slope b
.
Estimates a response y
given a predictor x
and a set of predictors and responses, i.e.
it calculates y
in y:x↦a+bx
.
Measures how close the observed data are to the fitted regression line, i.e. how accurate the prediction is given the actual data.
Returns a value between 0 and 1 where 0 indicates a prediction that is worse than the mean and 1 indicates a perfect prediction.