Spatial Model - Irregular Grid
See Also
This menu provides facilities for the analysis of one- or two-dimensional data in the form of a grid using the method of residual maximum likelihood (REML), which is also sometimes called restricted maximum likelihood. The data should be supplied in a single variate with variate(s) to specify the Y positions and X positions.

Data

Specifies a variate containing the data values.

Y Positions

A variate specifying the Y coordinates in the grid.

X Positions

A variate specifying the X positions in the grid. This is only required when you have two-dimensional data.

Model

Lists the available correlation models. Select the correlation model that you want to apply to the grid.

Distance Measure

Lists the distance measures that are available for the power correlation model. Select the distance measure that you want to apply.

Form of Model

Allows the form of the model to be defined as either isotropic or anisotropic

Fixed Model

The fixed model describes imposed treatment factors and covariates for which the effect of specified levels or values are of interest. The model is described using a formula, which can combine main effects and interactions of factors and also covariates.

Random Model

The random model is generally used to describe those factors for which the values present in an experiment can be considered drawn from some large homogeneous population. The model is described using a formula, which can combine main effects and interactions of factors and also covariates.

Available Data

This lists data structures appropriate to the current input field. The contents will change as you move from one field to the next. Double-click on a name to copy it to the current input field; alternatively, you can type in the name directly.

Operators

This provides a quick way of entering operators in the fixed and random model formulas. Double-click on the required symbol to copy it to the current input field. You can also type in operators directly. See Operators in model formulae for a description of each.

See Also