In statistics, Whittle likelihood is an approximation to the likelihood function of a stationary Gaussian time series. It is named after the mathematician and statistician Peter Whittle, who introduced it in his PhD thesis in 1951.[1]
It is commonly used in time series analysis and signal processing for parameter estimation and signal detection.
^Whittle, P. (1951). Hypothesis testing in times series analysis. Uppsala: Almqvist & Wiksells Boktryckeri AB.
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In statistics, Whittlelikelihood is an approximation to the likelihood function of a stationary Gaussian time series. It is named after the mathematician...
In statistics, maximum likelihood estimation (MLE) is a method of estimating the parameters of an assumed probability distribution, given some observed...
The likelihood function (often simply called the likelihood) is the joint probability mass (or probability density) of observed data viewed as a function...
null = − 2 ln likelihood of null model likelihood of the saturated model D fitted = − 2 ln likelihood of fitted model likelihood of the saturated...
The most common case is maximum likelihood estimation, where the maximum likelihood estimate (MLE) maximizes likelihood (minimizes expected surprisal)...
variance. Estimates can be constructed using the maximum likelihood principle, the likelihood theory for this provides two ways of constructing confidence...
then θ {\displaystyle \theta } can be estimated by maximum likelihood. The maximum-likelihood estimates lack a closed-form expression and must be found...
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with lower BIC are generally preferred. It is based, in part, on the likelihood function and it is closely related to the Akaike information criterion...
Weighted least squares Generalized least squares Linear Template Fit Maximum likelihood estimation can be performed when the distribution of the error terms is...
statistical significance. Together with the Lagrange multiplier test and the likelihood-ratio test, the Wald test is one of three classical approaches to hypothesis...
given elsewhere. In case of missing data, Garren derived the maximum likelihood estimator. Some distributions (e.g., stable distributions other than a...
consequences: the maximum likelihood estimates (MLE) of the parameters will usually be biased, as well as inconsistent (unless the likelihood function is modified...
ray-tracing (Matlab code). If the mean and covariance matrix are known, the log likelihood of an observed vector x {\displaystyle {\boldsymbol {x}}} is simply the...
partial likelihood, shown below, is obtained by using Breslow's estimate of the baseline hazard function, plugging it into the full likelihood and then...
Spectrogram Time–frequency analysis Time–frequency representation Whittlelikelihood Spectral power distribution P Stoica and R Moses, Spectral Analysis...
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