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CharacteristicPolynomial   (Built-in Mathematica Symbol)
CharacteristicPolynomial[m, x] gives the characteristic polynomial for the matrix m. CharacteristicPolynomial[{m, a}, x] gives the generalized characteristic polynomial with ...
Listable   (Built-in Mathematica Symbol)
Listable is an attribute that can be assigned to a symbol f to indicate that the function f should automatically be threaded over lists that appear as its arguments.
ParallelSubmit   (Built-in Mathematica Symbol)
ParallelSubmit[expr] submits expr for evaluation on the next available parallel kernel and returns an EvaluationObject expression representing the submitted ...
ProteinData   (Built-in Mathematica Symbol)
ProteinData["prot"] gives the reference amino acid sequence for the protein prot.ProteinData["prot", " property"] gives the value of the specified property for the protein ...
Subsets   (Built-in Mathematica Symbol)
Subsets[list] gives a list of all possible subsets of list. Subsets[list, n] gives all subsets containing at most n elements. Subsets[list, {n}] gives all subsets containing ...
Convolutions and Correlations   (Mathematica Tutorial)
Convolution and correlation are central to many kinds of operations on lists of data. They are used in such areas as signal and image processing, statistical data analysis, ...
The Mathematica function DSolve finds symbolic solutions to differential equations. (The Mathematica function NDSolve, on the other hand, is a general numerical differential ...
Sparse Arrays: Manipulating Lists   (Mathematica Tutorial)
Lists are normally specified in Mathematica just by giving explicit lists of their elements. But particularly in working with large arrays, it is often useful instead to be ...
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, ...}, ...}] ...
SparseArray   (Built-in Mathematica Symbol)
SparseArray[{pos_1 -> val_1, pos_2 -> val_2, ...}] yields a sparse array in which values val_i appear at positions pos_i. SparseArray[{pos_1, pos_2, ...} -> {val_1, val_2, ...
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