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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,Expand
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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 theExpand
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Model uncertainty, data mining and statistical inference
This paper takes a broad, pragmatic view of statistical inference to include all aspects of model formulation. The estimation of model parameters traditionally assumes that a model has a prespecifiedExpand
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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 commonExpand
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Statistics for Technology.
Statistics for technology , Statistics for technology, مرکز فناوری اطلاعات و رسانی . Expand
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Statistics for physicists
Statistics for Physicists. By B. R. Martin. London, Academic Press, 1971. xiii, 209 p. 914″. £3·50.
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The Analysis of Time Series: An Introduction
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. Expand
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Probability and statistics in engineering and management science
Probability and Statistics in Engineering and Management Science. By William W. Hines and Douglas C. Montgomery. New York, The Ronald Press Co., 1972. xii, 509 p. 914″. $13.50.
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19. Statistical Analysis with Missing Data
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The M2-competition: A real-time judgmentally based forecasting study
The purpose of the M2-Competition is to determine the post sample accuracy of various forecasting methods. It is an empirical study organized in such a way as to avoid the major criticism of theExpand
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