SQL functions for linear regression. More...

Functions
void	robust_input_checking (varchar source_table, varchar out_table, varchar dependent_varname, varchar independent_varname)

bytea8	robust_linregr_transition (bytea8 state, float8 y, float8[] x, float8[] coef)

bytea8	robust_linregr_merge_states (bytea8 state1, bytea8 state2)

robust_linregr_result	robust_linregr_final (bytea8 state)

aggregate robust_linregr_result	robust_linregr (float8 dependentVariable, float8[] independentVariables, float8[] coef)
	Compute robust regression diagnostic statistics for linear regression. More...

CREATE FUNCTION MADlib	__internal_get_robust_linregr_result (source_table VARCHAR--name of input table, dependent_varname VARCHAR--name of dependent variable, independent_varname VARCHAR--name of independent variable, linregr_coeffs DOUBLE PRECISION[]--coeffs from linear regression) RETURNS MADlib.robust_linregr_result AS $$DECLARE robust_value MADlib.robust_linregr_result
	Return robust linear regression estimates given a set of coefficients. More...

BEGIN EXECUTE	SELECT (MADlib.robust_linregr('\|\|dependent_varname\|\| ', '\|\|independent_varname\|\| ', '\|\| 'ARRAY['\|\|array_to_string(linregr_coeffs, ',')\|\| '])).*FROM '\|\|source_table INTO robust_value

CREATE FUNCTION MADlib	__internal_get_robust_linregr_insert_string (robust_lin_rst MADlib.robust_linregr_result, linregr_coeffs DOUBLE PRECISION[]--coeffs from linear regression, out_table TEXT) RETURNS VARCHAR AS $$DECLARE insert_string VARCHAR
	Return insert string for robust linear regression. More...

insert_string ELSE END CASE	WHEN (robust_lin_rst).std_err is NULL THEN '''

Interface CREATE OR REPLACE FUNCTION MADlib	robust_variance_linregr (usage_string VARCHAR--usage string) RETURNS VARCHAR AS $$DECLARE insert_string VARCHAR

CREATE OR REPLACE FUNCTION MADlib	robust_variance_linregr () RETURNS VARCHAR AS $$BEGIN RETURN MADlib.robust_variance_linregr('')

CREATE OR REPLACE FUNCTION MADlib	robust_variance_linregr (source_table VARCHAR--name of input table, out_table VARCHAR--name of output table, dependent_variable VARCHAR--name of dependent variable, independent_variable VARCHAR--name of independent variable) RETURNS VOID AS $$BEGIN PERFORM MADlib.robust_variance_linregr(source_table
	Robust linear regression with default fit regression behaviour & no grouping. More...

Robust Linear Regression CREATE OR REPLACE FUNCTION MADlib	robust_variance_linregr (source_table VARCHAR--name of input table, out_table VARCHAR--name of output table, dependent_varname VARCHAR--name of dependent variable, input_independent_varname VARCHAR--name of independent variable, input_group_cols VARCHAR--grouping columns) RETURNS VOID AS $$DECLARE insert_string VARCHAR
	Robust linear regression function subcall. More...

PERFORM MADlib	robust_input_checking (source_table, out_table, dependent_varname, input_independent_varname)

This code should be added back in should *support be implemented float8[]	robust_logregr_step_transition (float8[] state, boolean y, float8[] x, float8[] coef)

float8[]	robust_logregr_step_merge_states (float8[] state1, float8[] state2)

robust_logregr_result	robust_logregr_step_final (float8[] state)

aggregate robust_logregr_result	robust_logregr (boolean dependentVariable, float8[] independentVariables, float8[] coef)
	Compute robust regression diagnostic statistics for logistic regression. More...

CREATE FUNCTION MADlib	__internal_get_robust_logregr_result (source_table VARCHAR--name of input table, dependent_varname VARCHAR--name of dependent variable, independent_varname VARCHAR--name of independent variable, logregr_coeffs DOUBLE PRECISION[]--coeffs from logear regression) RETURNS MADlib.robust_logregr_result AS $$DECLARE robust_value MADlib.robust_logregr_result
	Return robust logistic regression estimates given a set of coefficients. More...

BEGIN EXECUTE	SELECT (MADlib.robust_logregr(('\|\|dependent_varname\|\| ')::BOOLEAN, '\|\|independent_varname\|\| ', '\|\| 'ARRAY['\|\|array_to_string(logregr_coeffs, ',')\|\| '])).*FROM '\|\|source_table INTO robust_value

CREATE FUNCTION MADlib	__internal_get_robust_logregr_insert_string (robust_log_rst MADlib.robust_logregr_result, out_table TEXT) RETURNS VARCHAR AS $$DECLARE insert_string VARCHAR
	Return insert string for robust logistic regression. More...

insert_string ELSE END CASE	WHEN (robust_log_rst).std_err is NULL THEN '''

Interface CREATE OR REPLACE FUNCTION MADlib	robust_variance_logregr (usage_string VARCHAR--usage string) RETURNS VARCHAR AS $$DECLARE insert_string VARCHAR

CREATE OR REPLACE FUNCTION MADlib	robust_variance_logregr () RETURNS VARCHAR AS $$BEGIN RETURN MADlib.robust_variance_logregr('')

void	robust_variance_logregr (varchar source_table, varchar out_table, varchar dependent_varname, varchar input_independent_varname, varchar input_group_cols, integer max_iter, varchar optimizer, float8 tolerance, boolean print_warnings)
	The robust logistic regression function. More...

CREATE OR REPLACE FUNCTION MADlib	robust_variance_logregr (source_table VARCHAR,--name of input table out_table VARCHAR,--name of output table dependent_variable VARCHAR,--name of dependent variable independent_variable VARCHAR,--name of independent variable input_group_cols VARCHAR--grouping columns) RETURNS VOID AS $$BEGIN PERFORM MADlib.robust_variance_logregr(source_table
	Robust logistic function subcall. More...

CREATE OR REPLACE FUNCTION MADlib	robust_variance_logregr (source_table VARCHAR--name of input table, out_table VARCHAR--name of output table, dependent_variable VARCHAR--name of dependent variable, independent_variable VARCHAR--name of independent variable) RETURNS VOID AS $$BEGIN PERFORM MADlib.robust_variance_logregr(source_table
	Robust logistic regression with default fit regression behavior, and no grouping,. More...

CREATE OR REPLACE FUNCTION MADlib	robust_variance_logregr (source_table VARCHAR--name of input table, out_table VARCHAR--name of output table, dependent_variable VARCHAR--name of dependent variable, independent_variable VARCHAR--name of independent variable, input_group_cols VARCHAR--grouping columns, max_iter INTEGER--max number of iterations) RETURNS VOID AS $$BEGIN PERFORM MADlib.robust_variance_logregr(source_table

CREATE OR REPLACE FUNCTION MADlib	robust_variance_logregr (source_table VARCHAR--name of input table, out_table VARCHAR--name of output table, dependent_variable VARCHAR--name of dependent variable, independent_variable VARCHAR--name of independent variable, input_group_cols VARCHAR--grouping columns, max_iter INTEGER--max number of iterations, optimizer VARCHAR--The optimizer used in the robust regression) RETURNS VOID AS $$BEGIN PERFORM MADlib.robust_variance_logregr(source_table

CREATE OR REPLACE FUNCTION MADlib	robust_variance_logregr (source_table VARCHAR--name of input table, out_table VARCHAR--name of output table, dependent_variable VARCHAR--name of dependent variable, independent_variable VARCHAR--name of independent variable, input_group_cols VARCHAR--grouping columns, max_iter INTEGER--max number of iterations, optimizer VARCHAR--The optimizer used in the robust regression, tolerance DOUBLE PRECISION--The tolerance of the optimizer) RETURNS VOID AS $$BEGIN PERFORM MADlib.robust_variance_logregr(source_table

ROBUST MULTINOMIAL LOGISTIC REGRESSION CREATE TYPE MADlib robust_mlogregr_result	AS (ref_category INTEGER, coef DOUBLE PRECISION[], std_err DOUBLE PRECISION[], z_stats DOUBLE PRECISION[], p_values DOUBLE PRECISION[])

CREATE OR REPLACE FUNCTION MADlib	mlogregr_robust_step_transition (state DOUBLE PRECISION[], y INTEGER, numCategories INTEGER, ref_category INTEGER, x DOUBLE PRECISION[], coef DOUBLE PRECISION[]) RETURNS DOUBLE PRECISION[] AS 'MODULE_PATHNAME'LANGUAGE C IMMUTABLE

CREATE OR REPLACE FUNCTION MADlib	mlogregr_robust_step_merge_states (state1 DOUBLE PRECISION[], state2 DOUBLE PRECISION[]) RETURNS DOUBLE PRECISION[] AS 'MODULE_PATHNAME'LANGUAGE C IMMUTABLE STRICT

CREATE OR REPLACE FUNCTION MADlib	mlogregr_robust_step_final (state DOUBLE PRECISION[]) RETURNS MADlib.robust_mlogregr_result AS 'MODULE_PATHNAME'LANGUAGE C IMMUTABLE STRICT

void	robust_variance_mlogregr (varchar source_table, varchar out_table, varchar dependent_varname, varchar independent_varname, integer ref_category, varchar input_group_cols, integer max_iter, varchar optimizer, float8 tolerance, boolean print_warnings)
	Compute robust regression diagnostic statistics for multinomial logistic regression. More...

Variables
RETURN	robust_value

END LANGUAGE plpgsql	VOLATILE

BEGIN	insert_string

insert_string	__pad0__

insert_string ELSE	ARRAY ['\|\|array_to_string(linregr_coeffs, ',')\|\| ']

ELSE ARRAY['\|\|array_to_string((robust_lin_rst).p_values, ',')\|\| ']	END

BEGIN IF(usage_string= ''OR usage_string= 'help'OR usage_string= '?') THEN insert_string n E For more details on function	usage

ELSIF(usage_string= 'usage') THEN insert_string n E n E	Output

ELSIF(usage_string= 'usage') THEN insert_string n E n E Coefficients of regression n E std_err DOUBLE	PRECISION []

ELSIF(usage_string= 'usage') THEN insert_string n E n E Coefficients of regression n E std_err DOUBLE Huber White standard errors n E stats DOUBLE T stats of the standard errors n E p_values DOUBLE p values of the standard errors n E n	E

END	IF

CREATE OR REPLACE FUNCTION MADlib	out_table

CREATE OR REPLACE FUNCTION MADlib	dependent_variable

CREATE OR REPLACE FUNCTION MADlib	independent_variable

CREATE OR REPLACE FUNCTION MADlib	NULL

group_cols	VARCHAR []

robust_lin_rst MADlib	robust_linregr_result

group_array_length	INTEGER

old_msg_level	TEXT

BEGIN EXECUTE SELECT setting FROM pg_settings WHERE	name =''client_min_messages''' INTO old_msg_level

EXECUTE SET client_min_messages TO	warning

independent_varname	__pad1__

insert_string	__pad2__

CREATE OR REPLACE FUNCTION MADlib	input_group_cols

CREATE OR REPLACE FUNCTION MADlib	irls

CREATE OR REPLACE FUNCTION MADlib	FALSE

CREATE OR REPLACE FUNCTION MADlib	max_iter

CREATE OR REPLACE FUNCTION MADlib	optimizer

CREATE OR REPLACE FUNCTION MADlib	tolerance

Detailed Description

Date: January 2011

See Also: Calculates robust statistics for various regression models.

Function Documentation

CREATE FUNCTION MADlib __internal_get_robust_linregr_insert_string	(	robust_lin_rst MADlib.	robust_linregr_result,
		linregr_coeffs DOUBLE PRECISION--[]coeffs from linear	regression,
		out_table	TEXT
	)

CREATE FUNCTION MADlib __internal_get_robust_linregr_result	(	source_table VARCHAR--name of input	table,
		dependent_varname VARCHAR--name of dependent	variable,
		independent_varname VARCHAR--name of independent	variable,
		linregr_coeffs DOUBLE PRECISION--[]coeffs from linear	regression
	)

CREATE FUNCTION MADlib __internal_get_robust_logregr_insert_string	(	robust_log_rst MADlib.	robust_logregr_result,
		out_table	TEXT
	)

CREATE FUNCTION MADlib __internal_get_robust_logregr_result	(	source_table VARCHAR--name of input	table,
		dependent_varname VARCHAR--name of dependent	variable,
		independent_varname VARCHAR--name of independent	variable,
		logregr_coeffs DOUBLE PRECISION--[]coeffs from logear	regression
	)

ROBUST MULTINOMIAL LOGISTIC REGRESSION CREATE TYPE MADlib robust_mlogregr_result AS	(	ref_category	INTEGER,
		coef DOUBLE	PRECISION[],
		std_err DOUBLE	PRECISION[],
		z_stats DOUBLE	PRECISION[],
		p_values DOUBLE	PRECISION[]
	)

CREATE OR REPLACE FUNCTION MADlib mlogregr_robust_step_final ( state DOUBLE PRECISION[])

CREATE OR REPLACE FUNCTION MADlib mlogregr_robust_step_merge_states	(	state1 DOUBLE	PRECISION[],
		state2 DOUBLE	PRECISION[]
	)

CREATE OR REPLACE FUNCTION MADlib mlogregr_robust_step_transition	(	state DOUBLE	PRECISION[],
		y	INTEGER,
		numCategories	INTEGER,
		ref_category	INTEGER,
		x DOUBLE	PRECISION[],
		coef DOUBLE	PRECISION[]
	)

void robust_input_checking	(	varchar	source_table,
		varchar	out_table,
		varchar	dependent_varname,
		varchar	independent_varname
	)

PERFORM MADlib robust_input_checking	(	source_table	,
		out_table	,
		dependent_varname	,
		input_independent_varname
	)

aggregate robust_linregr_result robust_linregr	(	float8	dependentVariable,
		float8[]	independentVariables,
		float8[]	coef
	)

Parameters

dependentVariable	Column containing the dependent variable
independentVariables	Column containing the array of independent variables
coef	Column containing the array of the OLS coefficients (as obtained by linregr)

: To include an intercept in the model, set one coordinate in the independentVariables array to 1.

Returns

A composite value:

std_err FLOAT8[] - Array of huber-white standard errors, $ \mathit{se}(c_1), \dots, \mathit{se}(c_k) $
t_stats FLOAT8[] - Array of t-statistics, $ \boldsymbol t $
p_values FLOAT8[] - Array of p-values, $ \boldsymbol p $

Usage

Get all the diagnostic statistics:

 SELECT (robust_linregr(dependentVariable,
    independentVariables, coef)).*
    FROM (
    SELECT linregr(dependentVariable, independentVariables).coef
    ) AS ols_coef, sourceName as src;

Get a subset of the output columns, e.g., only the condition number and the array of p-values $ \boldsymbol p $:

SELECT (lr).robust_condition_no, (lr).robust_p_values
FROM (

 SELECT (robust_linregr(dependentVariable,
    independentVariables, coef)).*
    FROM (
    SELECT linregr(dependentVariable, independentVariables).coef
    ) AS ols_coef, sourceName as src
) AS subq;

robust_linregr_result robust_linregr_final ( bytea8 state)

bytea8 robust_linregr_merge_states	(	bytea8	state1,
		bytea8	state2
	)

bytea8 robust_linregr_transition	(	bytea8	state,
		float8	y,
		float8[]	x,
		float8[]	coef
	)

aggregate robust_logregr_result robust_logregr	(	boolean	dependentVariable,
		float8[]	independentVariables,
		float8[]	coef
	)

Parameters

dependentVariable	Column containing the dependent variable
independentVariables	Column containing the array of independent variables
coef	Column containing the array of the coefficients (as obtained by logregr)

: To include an intercept in the model, set one coordinate in the independentVariables array to 1.

Returns

A composite value:

coef FLOAT8[] - The coefficients for the regression
std_err FLOAT8[] - Array of huber-white standard errors, $ \mathit{se}(c_1), \dots, \mathit{se}(c_k) $
z_stats FLOAT8[] - Array of Wald z-statistics, $ \boldsymbol t $
p_values FLOAT8[] - Array of p-values, $ \boldsymbol p $

Usage

Get all the diagnostic statistics:

 SELECT robust_logregr(dependentVariable,
 independentVariables, coef)
 FROM dataTable;

robust_logregr_result robust_logregr_step_final ( float8[] state)

float8 [] robust_logregr_step_merge_states	(	float8[]	state1,
		float8[]	state2
	)

This code should be added back in should* support be implemented float8 [] robust_logregr_step_transition	(	float8[]	state,
		boolean	y,
		float8[]	x,
		float8[]	coef
	)

Interface CREATE OR REPLACE FUNCTION MADlib robust_variance_linregr ( usage_string VARCHAR--usage string)

CREATE OR REPLACE FUNCTION MADlib robust_variance_linregr ( )

CREATE OR REPLACE FUNCTION MADlib robust_variance_linregr	(	source_table VARCHAR--name of input	table,
		out_table VARCHAR--name of output	table,
		dependent_variable VARCHAR--name of dependent	variable,
		independent_variable VARCHAR--name of independent	variable
	)

Robust Linear Regression CREATE OR REPLACE FUNCTION MADlib robust_variance_linregr	(	source_table VARCHAR--name of input	table,
		out_table VARCHAR--name of output	table,
		dependent_varname VARCHAR--name of dependent	variable,
		input_independent_varname VARCHAR--name of independent	variable,
		input_group_cols VARCHAR--grouping	columns
	)

Interface CREATE OR REPLACE FUNCTION MADlib robust_variance_logregr ( usage_string VARCHAR--usage string)

CREATE OR REPLACE FUNCTION MADlib robust_variance_logregr ( )

void robust_variance_logregr	(	varchar	source_table,
		varchar	out_table,
		varchar	dependent_varname,
		varchar	input_independent_varname,
		varchar	input_group_cols,
		integer	max_iter,
		varchar	optimizer,
		float8	tolerance,
		boolean	print_warnings
	)

Parameters

source_table	String identifying the input table
out_table	String identifying the output table to be created
dependent_varname	Column containing the dependent variable
independent_varname	Column containing the array of independent variables
input_group_cols	Columns to group by.
max_iter	Integer identifying the maximum iterations used by the logistic regression solver. Default is 20.
optimizer	String identifying the optimizer used in the logistic regression. See the documentation in the logistic regression for the available options. Default is irls.
tolerance	Float identifying the tolerance of the logistic regression optimizer. Default is 0.0001.
print_warnings	Boolean specifying if the regression fit should print any warning messages. Default is false.

: To include an intercept in the model, set one coordinate in the independent_varname array to 1.

Returns

A composite value:

std_err FLOAT8[] - Array of huber-white standard errors, $ \mathit{se}(c_1), \dots, \mathit{se}(c_k) $
t_stats FLOAT8[] - Array of t-statistics, $ \boldsymbol t $
p_values FLOAT8[] - Array of p-values, $ \boldsymbol p $

Usage

For function summary information. Run sql> select robust_variance_logregr('help'); OR sql> select robust_variance_logregr(); OR sql> select robust_variance_logregr('?'); For function usage information. Run sql> select robust_variance_logregr('usage');

Compute the coefficients, and the get the robust diagnostic statistics:

   select robust_variance_logregr(source_table, out_table, regression_type, dependentVariable, independentVariables, NULL );

If the coefficients are already known, they can be provided directly

select robust_variance_logregr(source_table, out_table, regression_type, dependentVariable, independentVariables, coef );

CREATE OR REPLACE FUNCTION MADlib robust_variance_logregr	(	source_table	VARCHAR,
		--name of input table out_table	VARCHAR,
		--name of output table dependent_variable	VARCHAR,
		--name of dependent variable independent_variable	VARCHAR,
		--name of independent variable input_group_cols VARCHAR--grouping	columns
	)

CREATE OR REPLACE FUNCTION MADlib robust_variance_logregr	(	source_table VARCHAR--name of input	table,
		out_table VARCHAR--name of output	table,
		dependent_variable VARCHAR--name of dependent	variable,
		independent_variable VARCHAR--name of independent	variable
	)

CREATE OR REPLACE FUNCTION MADlib robust_variance_logregr	(	source_table VARCHAR--name of input	table,
		out_table VARCHAR--name of output	table,
		dependent_variable VARCHAR--name of dependent	variable,
		independent_variable VARCHAR--name of independent	variable,
		input_group_cols VARCHAR--grouping	columns,
		max_iter INTEGER--max number of	iterations
	)

CREATE OR REPLACE FUNCTION MADlib robust_variance_logregr	(	source_table VARCHAR--name of input	table,
		out_table VARCHAR--name of output	table,
		dependent_variable VARCHAR--name of dependent	variable,
		independent_variable VARCHAR--name of independent	variable,
		input_group_cols VARCHAR--grouping	columns,
		max_iter INTEGER--max number of	iterations,
		optimizer VARCHAR--The optimizer used in the robust	regression
	)

CREATE OR REPLACE FUNCTION MADlib robust_variance_logregr	(	source_table VARCHAR--name of input	table,
		out_table VARCHAR--name of output	table,
		dependent_variable VARCHAR--name of dependent	variable,
		independent_variable VARCHAR--name of independent	variable,
		input_group_cols VARCHAR--grouping	columns,
		max_iter INTEGER--max number of	iterations,
		optimizer VARCHAR--The optimizer used in the robust	regression,
		tolerance DOUBLE PRECISION--The tolerance of the	optimizer
	)

void robust_variance_mlogregr	(	varchar	source_table,
		varchar	out_table,
		varchar	dependent_varname,
		varchar	independent_varname,
		integer	ref_category,
		varchar	input_group_cols,
		integer	max_iter,
		varchar	optimizer,
		float8	tolerance,
		boolean	print_warnings
	)

Parameters

source_table	name of input table, VARCHAR
out_table	name of output table, VARCHAR
dependent_varname	dependent variable, VARCHAR
independent_varname	independent variables, VARCHAR
ref_category	Integer specifying the reference category. Default is 0.
grouping_cols	grouping variables, VARCHAR. Default is NULL. Currently a placeholder.
max_iter	Integer identifying the maximum iterations used by the logistic regression solver. Default is 20.
optimizer	String identifying the optimizer used in the multinomial logistic regression. See the documentation in the multinomial logistic regression for the available options. Default is 'irls'.
tolerance	Float identifying the tolerance of the multinomial logistic regression optimizer. Default is 0.0001.
print_warnings	Boolean specifying if the multinomial logistic regression solver should print any warnings. Currently a placeholder.

: To include an intercept in the model, set one coordinate in the independentVariables array to 1.

Usage

SELECT  madlib.robust_variance_mlogregr(
    'source_table',        -- name of input table, VARCHAR
    'out_table',           -- name of output table, VARCHAR
    'dependent_varname',   -- dependent variable, VARCHAR
    'independent_varname', -- independent variables, VARCHAR
    ref_category,        -- [OPTIONAL] Integer specifying the reference category. Default is 0.
    'grouping_cols',       -- [OPTIONAL] grouping variables, VARCHAR. Default is NULL.
    max_iter,          -- [OPTIONAL] Integer identifying the maximum iterations used by the logistic regression solver.  Default is 20.
    'optimizer',           -- [OPTIONAL] String identifying the optimizer used in the multinomial logistic regression.  See the documentation in the multinomial logistic regression for the available options.  Default is irls.
    tolerance,         -- [OPTIONAL] Float identifying the tolerance of the multinomial logistic regression optimizer. Default is 0.0001.
    print_warnings     -- [OPTIONAL] Boolean specifying if the regression fit should print any warning messages.  Default is false.
);

Returns

A composite value:

ref_category INTEGER - The reference category
coef FLOAT8[] - The coefficients for the regression
std_err FLOAT8[] - Array of huber-white standard errors,
z_stats FLOAT8[] - Array of Wald z-statistics,
p_values FLOAT8[] - Array of p-values,

BEGIN EXECUTE SELECT ( MADlib. robust_linregr'||dependent_varname|| ', '||independent_varname|| ', '|| 'ARRAY['||array_to_string(linregr_coeffs, ',')|| '])

BEGIN EXECUTE SELECT ( MADlib. robust_logregr('||dependent_varname|| ')::BOOLEAN, '||independent_varname|| ', '|| 'ARRAY['||array_to_string(logregr_coeffs, ',')|| '])

ELSE END CASE WHEN ( robust_lin_rst )

ELSE END CASE WHEN ( robust_log_rst )

Variable Documentation

insert_string __pad0__

independent_varname __pad1__

insert_string __pad2__

ELSE ARRAY

CREATE OR REPLACE FUNCTION MADlib dependent_variable

ELSIF (usage_string = 'usage') THEN insert_string n E n E Coefficients of regression n E std_err DOUBLE Huber White standard errors n E stats DOUBLE Z stats of the standard errors n E p_values DOUBLE p values of the standard errors n E n E

END

CREATE OR REPLACE FUNCTION MADlib FALSE

END IF

CREATE OR REPLACE FUNCTION MADlib independent_variable

CREATE OR REPLACE FUNCTION MADlib input_group_cols

RETURN insert_string

each_group INTEGER

CREATE OR REPLACE FUNCTION MADlib irls

CREATE OR REPLACE FUNCTION MADlib max_iter

BEGIN EXECUTE SELECT setting FROM pg_settings WHERE name =''client_min_messages''' INTO old_msg_level

CREATE OR REPLACE FUNCTION MADlib NULL

CREATE OR REPLACE FUNCTION MADlib optimizer

CREATE OR REPLACE FUNCTION MADlib out_table

ELSIF (usage_string = 'usage') THEN insert_string n E n E Output

regr_coef DOUBLE PRECISION

robust_lin_rst MADlib robust_linregr_result

RETURN robust_value

old_msg_level TEXT

CREATE OR REPLACE FUNCTION MADlib tolerance

BEGIN IF (usage_string = '' OR usage_string = 'help' OR usage_string = '?') THEN insert_string n E For more details on function usage

independent_varname VARCHAR

LANGUAGE plpgsql VOLATILE

EXECUTE SET client_min_messages TO warning

Functions

Variables

Detailed Description

Function Documentation

Variable Documentation