A list of named values that matches the messages sent to ARIMA Forecast(). If you perform an ARIMA Forecast and save the script, the estimates are part of the script.

Define the range of values. Typically, from is between 1 and to, inclusive. If from is less than or equal to 0, and if from is less than or equal to to, the results include filtered predictions.

Optional: A By variable to compute statistics across groups of rows. Use the By variable in a column formula or in a For Each Row() function.

If a data value is assigned by a column property (such as Missing Value Codes), use Col Stored Value() to base the calculation on the value stored in the column instead. See Col Stored Value(<dt>, col, <row>).

Optional: A By variable to compute statistics across groups of rows. Use the By variable in a column formula or in a For Each Row() function.

If a data value is assigned by a column property (such as Missing Value Codes), use Col Stored Value() to base the calculation on the value stored in the column instead. See Col Stored Value(<dt>, col, <row>).

Optional: A By variable to compute statistics across groups of rows. Use the By variable in a column formula or in a For Each Row() function.

If a data value is assigned by a column property (such as Missing Value Codes), use Col Stored Value() to base the calculation on the value stored in the column instead. See Col Stored Value(<dt>, col, <row>).

Calculates the specified quantile p across all rows of the specified column. The result is internally cached to speed up multiple evaluations.

a specified quantile p between 0 and 1.

Using Big Class.jmp:

Calculates the sum across rows in a column. Calculating all missing values (Col Sum(.,.)) returns missing. The result is internally cached to speed up multiple evaluations.

Fit Censored(Distribution("name"), YLow(vector) | Y(Vector), <YHigh(vector)>, <Weight(vector)>, <X(matrix)>, <Z(matrix)>, <HoldParm(vector)>)

If you do not have censoring, then use Y and an array of your data, and do not specify YHigh. If you do have censoring, then specify YLow and YHigh as the lower and upper censoring values, respectively.

Must be a vector of the same length as vector, and can contain any nonnegative real numbers. Weights represents frequencies, counts, or similar concepts.

n must be 0, 1, 2, or 3, corresponding to Sheather and Jones, Normal Reference, Silverman rule of thumb, or Oversmoother, respectively.

n must be 0, 1, 2, 3, or 4, corresponding to Gaussian, Epanechnikov, Biweight, Triangular, or Rectangular, respectively.

Quantile of the arguments, where p is a value between 0 and 1, and the arguments are numbers, lists of numbers, or matrices.

Rowwise sum of the variables specified. Calculating all missing values (Sum(.,.))returns missing.

A data table of p-values and LogWorth values for each Y and X combination. See the Response Screening chapter in Specialized Models.

Performs the same function as the Response Screening platform. See Specialized Models for details.