SAGA.statistics_regression.8: Multiple Regression Analysis (Grid and Predictor Grids)

Linear regression analysis of one grid as dependent and multiple grids as indepentent (predictor) variables. Details of the regression/correlation analysis will be saved to a table. Optionally the regression model is used to create a new grid with regression based values. The multiple regression analysis uses a forward selection procedure. <br/><br/>Reference:<br/>- Bahrenberg, G., Giese, E., Nipper, J. (1992): 'Statistische Methoden in der Geographie 2 - Multivariate Statistik', Stuttgart, 415p.<br/>

Inputs

Dependent Variable

format
href
Please set a value for DEPENDENT.

Predictors

format
href
Please set a value for PREDICTORS.

Resampling

string

Include X Coordinate

boolean

Include Y Coordinate

boolean

Method

string

Significance level (aka p-value) as threshold for automated predictor selection, given as percentage

number

Cross Validation

string

number of subsamples for k-fold cross validation

integer

Outputs

Regression

format
transmission

Residuals

format
transmission

Details: Coefficients

format
transmission

Details: Model

format
transmission

Details: Steps

format
transmission

Execution options

successUri
inProgressUri
failedUri

format

mode

Execute End Point

View the execution endpoint of a process.

View the alternative version in HTML.

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Last modified: Sat Feb 19 15:43:34 CET 2022