Name: Practical Time Series Analysis in Natural Sciences (en Inglés)
Price: 747.04 PEN
Availability: InStock
Author: Privalsky, Victor
ISBN: 9783031168901

portada Practical Time Series Analysis in Natural Sciences (en Inglés)

Formato

Libro Físico

Autor

Victor Privalsky

Editorial

Springer

Idioma

Inglés

N° páginas

199

Encuadernación

Tapa Dura

Dimensiones

23.6 x 15.8 x 1.6 cm

Peso

0.48 kg.

ISBN13

9783031168901

N° edición

2023rd

Categorías

Probabilidad y estadística
Astronomía, espacio y tiempo
Geofísica

Practical Time Series Analysis in Natural Sciences (en Inglés)

Victor Privalsky (Autor) · Springer · Tapa Dura

Libro Nuevo

S/ 747,04

S/ 1.494,09

Ahorras: S/ 747,04

50% descuento

Envío normal

Origen: Reino Unido (Costos de importación incluídos en el precio)

Se enviará desde nuestra bodega entre el Lunes 01 de Julio y el Viernes 12 de Julio.

Lo recibirás en cualquier lugar de Perú entre 2 y 5 días hábiles luego del envío.

Reseña del libro "Practical Time Series Analysis in Natural Sciences (en Inglés)"

This book presents an easy-to-use tool for time series analysis and allows the user to concentrate upon studying time series properties rather than upon how to calculate the necessary estimates. The two attached programs provide, in one run of the program, a time and frequency domain description of scalar or multivariate time series approximated with a sequence of autoregressive models of increasing orders. The optimal orders are chosen by five order selection criteria. The results for scalar time series include time domain stochastic difference equations, spectral density estimates, predictability properties, and a forecast of scalar time series based upon the Kolmogorov-Wiener theory. For the bivariate and trivariate time series, the results contain a time domain description with multivariate stochastic difference equations, statistical predictability criterion, and information for calculating feedback and Granger causality properties in the bivariate case. The frequency domain information includes spectral densities, ordinary, multiple, and partial coherence functions, ordinary and multiple coherent spectra, gain, phase, and time lag factors. The programs seem to be unique and using them does not require professional knowledge of theory of random processes. The book contains many examples including three from engineering.