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Time Series Modelling

Resumen/Descripción – provisto por la editorial

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Palabras clave – provistas por la editorial

time series; anomaly detection; unsupervised learning; kernel density estimation; missing data; multivariate time series; nonstationary; spectral matrix; local field potential; electric power; forecasting accuracy; machine learning; extended binomial distribution; INAR; thinning operator; time series of counts; unemployment rate; SARIMA; SETAR; Holt–Winters; ETS; neural network autoregression; Romania; integer-valued time series; bivariate Poisson INGARCH model; outliers; robust estimation; minimum density power divergence estimator; CUSUM control chart; INAR-type time series; statistical process monitoring; random survival rate; zero-inflation; cointegration; subspace algorithms; VARMA models; seasonality; finance; volatility fluctuation; Student’s t-process; entropy based particle filter; relative entropy; count data; time series analysis; Julia programming language; ordinal patterns; long-range dependence; multivariate data analysis; limit theorems; integer-valued moving average model; counting series; dispersion test; Bell distribution; count time series; estimation; overdispersion; multivariate count data; INGACRCH; state-space model; bank failures; transactions; periodic autoregression; integer-valued threshold models; parameter estimation; models

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Información

Tipo de recurso:

libros

ISBN electrónico

978-3-0365-2122-0

País de edición

Suiza