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The Analysis of Time Series: An Introduction

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TLDR
In this paper, simple descriptive techniques for time series estimation in the time domain forecasting stationary processes in the frequency domain spectral analysis bivariate processes linear systems state-space models and the Kalman filter non-linear models multivariate time series modelling some other topics.
Abstract
Simple descriptive techniques probability models for time series estimation in the time domain forecasting stationary processes in the frequency domain spectral analysis bivariate processes linear systems state-space models and the Kalman filter non-linear models multivariate time series modelling some other topics.

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Calendar Effects in Monthly Time Series: Detection by Spectrum Analysis and Graphical Methods

TL;DR: Two sets of diagnostic methods for detecting calendar effects in monthly time series, spectrum analyses and time domain graphical displays, are described and can be used on an adjusted series to determine if the adjustment has properly removed all of the calendar effects.
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Regime-switching modelling of the fluctuations of offshore wind generation

TL;DR: In this article, the authors investigated the use of statistical regime-switching models for wind power generation and showed that the regime switching approach based on Markov-Switching autoregressive (MSAR) models significantly outperforms those based on observable regime sequences.
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Seabird ecology, el nino anomalies, and prediction of sardine fisheries in the gulf of california

TL;DR: Two statistical models that use oceanographic conditions and seabird breeding and feeding data to predict total fishery catch and catch per unit effort (CPUE) of Pacific sardine in the central Gulf show that the reproductive ecology of seabirds is coupled to the global and local oceanography conditions and that this can be used to predict in advance the outcome of fishing efforts.
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Prediction of summer temperature, rainfall and pressure in Europe from preceding winter North Atlantic Ocean temperature

TL;DR: In this paper, the authors examined the predictability of rainfall, surface temperature and pressure in Europe using a January-February North Atlantic SSTA pattern as predictor, and found that mean, minimum and maximum July-August temperatures over much of northwest Europe are predictable using linear regression with correlation skills in the range 0.4-0.7.
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The impact of large-scale forest harvesting on hydrology in the Willow watershed of Central British Columbia

TL;DR: In this article, the impacts of forest harvesting on peak, mean and low flows over annual and other periods (spring, summer and winter) were analyzed using various statistical techniques including time series analysis and non-parametric tests.