Identifies a column whose values assign a frequency to each row for the analysis. In general terms, the effect of a frequency column is to expand the data table, so that any row with integer frequency k is expanded to k rows. You are allowed to specify fractional frequencies. See Frequency.
ValidationIn JMP Pro, for some personalities, you can enter a Validation column. See the appropriate Personality chapter for details. If you click the Validation button with no columns selected in the Select Columns list, you can add a validation column to your data table. For more information about the Make Validation Column utility, see Make Validation Column Utility in the Predictive and Specialized Modeling book.
Applies the specified degree to models with factorial or polynomial effects generated using Macros. See Factorial to Degree and Polynomial to Degree in Macros.
Applies attributes to model effects. These attributes determine how the effects are treated. See Attributes.
Specifies the fitting methodology. See Fit Model Launch Window Elements. Different options appear depending on the personality that you select.
Frequency variables, entered in the Freq text box, are an option for most Fit Model personalities. In general, a frequency is interpreted as follows. Suppose that a row has a frequency f. Then the computed results are identical to those for a data table containing f copies of that row, each having a frequency of one.
Frequency values need not be integers. The technical details describing how frequency columns, including those with non-integer values, are handled are given in Frequencies.
Weight variables are an option for those Fit Model personalities where estimation is performed using least squares or normal theory maximum likelihood. In these cases, the weight w for a given row scales that row’s contribution to the loss function by w-1/2.