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Introduction to Statistical Time Series.
Moving Average and Autoregressive Processes. Introduction to Fourier Analysis. Spectral Theory and Filtering. Some Large Sample Theory. Estimation of the Mean and Autocorrelations. The Periodogram,
Model uncertainty, data mining and statistical inference
The effects of model uncertainty, such as too narrow prediction intervals, and the non-trivial biases in parameter estimates which can follow data-based modelling are reviewed.
Introduction To Multivariate Analysis
Part One. Multivariate distributions. Preliminary data analysis. Part Two: Finding new underlying variables. Principal component analysis. Factor analysis. Part Three: Procedures based on the
The Analysis of Time Series
The analysis of time series shows improvements in the quality of the data over time, particularly in the case of discrete-time series data.
Time‐series forecasting
Chris Chatfield looks at the chequered history of forecasting and asks how to do it better using time-series data, and what statistical techniques and models might help us.
Calculating Interval Forecasts
The distinction between a forecasting method and a forecasting model is expounded and some general comments are made as to why prediction intervals tend to be too narrow in practice to encompas...
The Holt-Winters Forecasting Procedure
The paper re-analyses seven series from the Newbold-Granger study for which Box-Jenkins forecasts were reported to be much superior to the (automatic) Holt-Winters forecasts, and makes suggestions regarding the implementation of the Holt- Winters procedure, including a choice of starting values.
The Dirichlet: A comprehensive model of buying behaviour
The Dirichlet model describes how frequently-bought branded consumer products like instant coffee or toothpaste are purchased when the market is stationary and unsegmented. This is the common