Transcription of TIME SERIES - University of Cambridge
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TIME SERIESC ontentsSyllabus .. iiiBooks .. iiiKeywords .. iv1 Models for time Time SERIES data .. Trend, seasonality, cycles and residuals .. Stationary processes .. Autoregressive processes .. Moving average processes .. White noise .. The turning point test .. 42 Models of stationary Purely indeterministic processes .. ARMA processes .. ARIMA processes .. Estimation of the autocovariance function .. Identifying a MA(q) process .. Identifying an AR(p) process .. Distributions of the ACF and PACF .. 83 Spectral The discrete Fourier transform .. The spectral density .. Analysing the effects of smoothing .. 124 Estimation of the The periodogram .. Distribution of spectral estimates .. The fast Fourier transform.
Time series analysis refers to problems in which observations are collected at regular time intervals and there are correlationsamong successive observations. Applications covervirtuallyallareasof Statisticsbut some of the most importantinclude economic and financial time series, and many areas of environmental or ecological data.
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