General Syntax Conventions: Regression Equations

All regression models have the same form; in general:

dependent variable = expression including independent variables

On the left side of the equation specify the dependent variable, on the right side specify the expression including independent variables and the parameters to be estimated.

  • Refer to variables either by their numbers (e.g., = v1 - v2) or name (e.g., = Retail - Cost)
  • All names that are not recognized by the program as variable names or valid reserved keywords are interpreted to be parameters.
  • Equations can contain logical expressions that involve constants, variables, parameters, or any mixture of the three. Logical expressions evaluate to 0 if they are false and to 1 if they are true; thus, models containing conditional expressions can be evaluated (see Example 2 for an example of a model with logical expressions).
  • Operators: Use parentheses to specify complex logical conditions (see above) or change the default precedence of the arithmetic and logical operators shown below.
  • Arithmetic Operators: +, -, *, /
  • Logical Operators: <, >, >=, <=, <> (unequal)

For logical and/or/not operators, use arithmetic operators (see Summary of STATISTICA Formula Syntax)

Parenthesis: ( )

Constants:Pi = 3.14..., Euler (e) = 2.71...

Functions:

abs(x) - absolute value of x log10(x) - common logarithm of x
arcsin(x) - arc sine of x sign(x) - sign of x: if x>0 then +1, if x<0 then -1, if x=0 remains 0
cos(x) - cosine of x sin(x) - sine of x
exp(x) - e to the power of x sinh(x) - hyperbolic sine of x
log(x) - natural logarithm of x sqrt(x) - square root of x
log2(x) - binary logarithm of x tan(x) - tangent of x
  • Distributions and their functions: Distribution functions can be used in custom regression models. For example:

y = b0 + b1*normal(log(x), 1, 2)

where b0 and b1 are the regression parameters to be estimated. For more information on the types of distributions available, see Distributions and their functions.

Note: If the value of any variable used in the formula is missing (in the current case), then the expression evaluates to missing data (for the current case). If any of the variables to be used in the model need to be transformed or rescaled before the estimation procedure, use the spreadsheet features. For data recoding, use the Recode Values of Variable dialog.