Linear and Nonlinear Filters (Mathematica Guide)

Mathematica's highly optimized filtering capabilities provide a wide range of linear and modern nonlinear local filters, as well as a variety of nonlocal filters, which can ...

Get Parts of an Image (Mathematica How To)

MATHEMATICA HOW TO Tutorials » Image Processing Convolutions and Correlations See Also » ImageCrop ImageTake More About » Raster Image Formats Signal Processing "How to" ...

Perform a Linear Regression (Mathematica How To)

One of the most common statistical models is the linear regression model. A linear model predicts the value of a response variable by the linear combination of predictor ...

ProbabilityDistribution (Built-in Mathematica Symbol)

ProbabilityDistribution[pdf, {x, x_min, x_max}] represents the continuous distribution with PDF pdf in the variable x where the pdf is taken to be zero for x < x_min and x > ...

HistogramDistribution (Built-in Mathematica Symbol)

HistogramDistribution[{x_1, x_2, ...}] represents the probability distribution corresponding to a histogram of the data values x_i.HistogramDistribution[{{x_1, y_1, ...}, ...

MarginalDistribution (Built-in Mathematica Symbol)

MarginalDistribution[dist, k] represents a univariate marginal distribution of the k\[Null]^th coordinate from the multivariate distribution dist.MarginalDistribution[dist, ...

UniformDistribution (Built-in Mathematica Symbol)

UniformDistribution[{min, max}] represents a continuous uniform statistical distribution giving values between min and max. UniformDistribution[] represents a uniform ...

FindDistributionParameters (Built-in Mathematica Symbol)

FindDistributionParameters[data, dist] finds the parameter estimates for the distribution dist from data.FindDistributionParameters[data, dist, {{p, p_0}, {q, q_0}, ...}] ...

Image Processing & Analysis (Mathematica Guide)

Mathematica provides broad and deep built-in support for both programmatic and interactive modern industrial-strength image processing —fully integrated with Mathematica's ...

SmoothKernelDistribution (Built-in Mathematica Symbol)

SmoothKernelDistribution[{x_1, x_2, ...}] represents a smooth kernel distribution based on the data values x_i.SmoothKernelDistribution[{{x_1, y_1, ...}, {x_2, y_2, ...}, ...