Title :
Model-based probability density function estimation
Author_Institution :
Dept. of Electr. & Comput. Eng., Rhode Island Univ., Kingston, RI, USA
Abstract :
Noting that the probability density function of a continuous random variable has similar properties to a power spectral density, a new class of probability density function estimators is described. The specific model examined is the autoregressive model, although the extension to other time series models is evident. An example is given to illustrate the approach.
Keywords :
autoregressive processes; parameter estimation; probability; random processes; spectral analysis; time series; autoregressive model; continuous random variable; power spectral density; probability density function estimation; time series models; Autocorrelation; Autoregressive processes; Density functional theory; Equations; Fourier transforms; Parameter estimation; Probability density function; Random variables; Spectral analysis; Tail;
Journal_Title :
Signal Processing Letters, IEEE
