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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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Travelling waves and spatial hierarchies in measles epidemics

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Interdecadal Variations of the Thermohaline Circulation in a Coupled Ocean-Atmosphere Model

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Exponential smoothing: the state of the art, part ii

TL;DR: Gardner as discussed by the authors reviewed the research in exponential smoothing since the original work by Brown and Holt and brought the state-of-the-art up to date by introducing a new class of state-space models with a single source of error.