Kernel Density Estimate

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• Kernel density estimation — of 100 normally distributed random numbers using different smoothing bandwidths. In statistics, kernel density estimation is a non parametric way of estimating the probability density function of a random variable. Kernel density estimation is a… …   Wikipedia

• Multivariate kernel density estimation — Kernel density estimation is a nonparametric technique for density estimation i.e., estimation of probability density functions, which is one of the fundamental questions in statistics. It can be viewed as a generalisation of histogram density… …   Wikipedia

• Density (disambiguation) — Density and dense usually refer to a measure of how much of some entity is within a fixed amount of space. Types of density include: In physics, density of mass: Density, mass per volume Area density or surface density, mass over a (two… …   Wikipedia

• Density estimation — In probability and statistics, density estimation is the construction of an estimate, based on observed data, of an unobservable underlying probability density function. The unobservable density function is thought of as the density according to… …   Wikipedia

• Kernel (statistics) — A kernel is a weighting function used in non parametric estimation techniques. Kernels are used in kernel density estimation to estimate random variables density functions, or in kernel regression to estimate the conditional expectation of a… …   Wikipedia

• Kernel regression — Not to be confused with Kernel principal component analysis. The kernel regression is a non parametric technique in statistics to estimate the conditional expectation of a random variable. The objective is to find a non linear relation between a… …   Wikipedia

• Kernel smoother — A kernel smoother is a statistical technique for estimating a real valued function f(X),,left( Xin mathbb{R}^{p} ight) by using its noisy observations, when no parametric model for this function is known. The estimated function is smooth, and the …   Wikipedia

• Stochastic kernel estimation — In statistics, a stochastic kernel estimate is an estimate of the transition function of a (usually discrete time) stochastic process. Often, this is an estimate of the conditional density function obtained using kernel density estimation. The… …   Wikipedia

• Bootstrapping (statistics) — In statistics, bootstrapping is a modern, computer intensive, general purpose approach to statistical inference, falling within a broader class of resampling methods.Bootstrapping is the practice of estimating properties of an estimator (such as… …   Wikipedia

• Box plot — In descriptive statistics, a boxplot (also known as a box and whisker diagram or plot) is a convenient way of graphically depicting groups of numerical data through their five number summaries (the smallest observation, lower quartile (Q1),… …   Wikipedia

• Psychometric software — is software that is used for psychometric analysis of data from tests, questionnaires, or inventories reflecting latent psychoeducational variables. While some psychometric analyses can be performed with standard statistical software like SPSS,… …   Wikipedia