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Sow   (Built-in Mathematica Symbol)
Sow[e] specifies that e should be collected by the nearest enclosing Reap. Sow[e, tag] specifies that e should be collected by the nearest enclosing Reap whose pattern ...
Regular Expressions   (Mathematica Tutorial)
General Mathematica patterns provide a powerful way to do string manipulation. But particularly if you are familiar with specialized string manipulation languages, you may ...
Plot Diagnostics for Fitted Models   (Mathematica How To)
Diagnostics are an important part of analyzing models of data. Plots of residuals and leverage or influence measures provide valuable insight into whether assumptions of the ...
BaselinePosition   (Built-in Mathematica Symbol)
BaselinePosition is an option that specifies where the baseline of an object is considered to be for purposes of alignment with surrounding text or other expressions.
ItemStyle   (Built-in Mathematica Symbol)
ItemStyle is an option for Grid, Column, and related constructs that specifies styles to use for items.
NonlinearModelFit   (Built-in Mathematica Symbol)
NonlinearModelFit[{y_1, y_2, ...}, form, {\[Beta]_1, ...}, x] constructs a nonlinear model with structure form that fits the y_i for successive x values 1, 2, ... using the ...
WignerSemicircleDistribution   (Built-in Mathematica Symbol)
WignerSemicircleDistribution[r] represents a Wigner semicircle distribution with radius r centered at the origin.WignerSemicircleDistribution[a, r] represents a Wigner ...
OpenCLFunctionLoad   (OpenCLLink Symbol)
OpenCLFunctionLoad[prog, fun, argtypes, blockdims] loads fun from source code prog, returning an OpenCLFunction object.OpenCLFunctionLoad[{progfile}, fun, argtypes, ...
EventLocator Method for NDSolve   (Mathematica Tutorial)
It is often useful to be able to detect and precisely locate a change in a differential system. For example, with the detection of a singularity or state change, the ...
LogitModelFit   (Built-in Mathematica Symbol)
LogitModelFit[{y_1, y_2, ...}, {f_1, f_2, ...}, x] constructs a binomial logistic regression model of the form 1/(1 + E -(\[Beta]_0 + \[Beta]_1 f_1 + \[Beta]_2 f_2 + \ ...)) ...
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