1741 - 1750 of 7976 for find in UnixSearch Results
View search results from all Wolfram sites (57499 matches)
MLPutShortInteger()   (Mathematica MathLink C Function)
int MLPutShortInteger (MLINK link, int i) puts the integer i to the MathLink connection specified by link, assuming that i contains only the number of digits in the C type ...
Exp   (Built-in Mathematica Symbol)
Exp[z] gives the exponential of z.
GraphData   (Built-in Mathematica Symbol)
GraphData[name] gives a graph with the specified name.GraphData[name, " property"] gives the value for the specified property for a named graph.GraphData["class"] gives a ...
MaxFilter   (Built-in Mathematica Symbol)
MaxFilter[image, r] filters image by replacing every value by the maximum in its range r neighborhood. MaxFilter[data, r] applies max filtering to an array of data.
MinFilter   (Built-in Mathematica Symbol)
MinFilter[image, r] filters image by replacing every value by the minimum in its range r neighborhood. MinFilter[data, r] applies min filtering to an array of data.
Files for Packages   (Mathematica Tutorial)
When you create or use Mathematica packages, you will often want to refer to files in a system-independent way. You can use contexts to do this. The basic idea is that on ...
SurvivalDistribution   (Built-in Mathematica Symbol)
SurvivalDistribution[{e_1, e_2, ...}] represents a survival distribution with event times e_i.SurvivalDistribution[{w_1, w_2, ...} -> {e_1, e_2, ...}] represents a survival ...
Ratios   (Built-in Mathematica Symbol)
Ratios[list] gives the successive ratios of elements in list. Ratios[list, n] gives the n\[Null]^th iterated ratios of list. Ratios[list, {n_1, n_2, ...}] gives the ...
CornerNeighbors   (Built-in Mathematica Symbol)
CornerNeighbors is an option for various array and image processing functions that specifies whether diagonally adjacent corners should be considered neighbors of particular ...
EmpiricalDistribution   (Built-in Mathematica Symbol)
EmpiricalDistribution[{x_1, x_2, ...}] represents an empirical distribution based on the data values x_i.EmpiricalDistribution[{{x_1, y_1, ...}, {x_2, y_2, ...}, ...}] ...
1 ... 172|173|174|175|176|177|178 ... 798 Previous Next

...