glm

swordfish.function.glm()

Fit a generalized linear model.

Parameters:

• ds (Constant) – The data source to be trained. It can be generated with function sqlDS.

• yColName (Constant) – A string indicating the dependent variable column.

• xColNames (Constant) – A STRING scalar/vector indicating the names of the indepenent variable columns.

• family (Constant,) – A string indicating the type of distribution. It can be gaussian (default), poisson, gamma, inverseGaussian or binomial.

• link (Constant, optional) –

  A string indicating the type of the link function.

  Possible values of link and the dependent variable for each family:

  family	link	default link	dependent variable
  gaussian	identity, inverse, log	identity	DOUBLE type
  poisson	log, sqrt, identity	log	non-negative integer
  gamma	inverse, identity, log	inverse	y>=0
  inverseGaussian	inverseOfSquare, inverse, identity, log | inverseOfSquare | y>=0
  binomial	logit, probit	logit	y=0,1

• tolerance (Constant, optional) – A numeric scalar. The iterations stops if the difference in the value of the log likelihood functions of 2 adjacent iterations is smaller than tolerance. The default value is 0.000001.

• maxIter (Constant, optional) – A positive integer indicating the maximum number of iterations. The default value is 100.

Returns:

A dictionary with the following keys: coefficients, link, tolerance, family, xColNames, tolerance, modelName, residualDeviance, iterations and dispersion.

• coefficients is a table with the coefficient estimate, standard deviation, t value and p value for each coefficient;

• modelName is “Generalized Linear Model”;

• iterations is the number of iterations;

• dispersion is the dispersion coefficient of the model.

Return type:

Constant