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Nonlinear regression with autoregressive errors
A. Ronald Gallant,J. J. Goebhel +1 more
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In this paper, an estimator of the parameters of a nonlinear time series regression when the statistical behavior of the disturbances can be reasonably approximated by an autoregressive model is presented.Abstract:
The article sets forth an estimator of the parameters of a nonlinear time series regression when the statistical behavior of the disturbances can be reasonably approximated by an autoregressive model. The sampling distribution of the estimator and relavent statistics is investigated both theoretically and using Monte-Carlo simulations.read more
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Organizational Environments in Flux: The Impact of Regulatory Punctuations on Organizational Domains, CEO Succession, and Performance
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A Structural Equations Analysis of the Impact of Price Promotions on Store Performance
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Market Response, Competitive Behavior, and Time Series Analysis:
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The solubility of aluminum in acidic forest soils: Long-term changes due to acid deposition
Jan Mulder,Alfred Stein +1 more
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New tests of the life cycle and tax discounting hypotheses
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References
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Time series analysis, forecasting and control
P. Young,S. Shellswell +1 more
TL;DR: Time series analysis san francisco state university, 6 4 introduction to time series analysis, box and jenkins time seriesAnalysis forecasting and, th15 weeks citation classic eugene garfield, proc arima references 9 3 sas support, time series Analysis forecasting and control pambudi, timeseries analysis forecasting and Control george e.
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Spectral analysis and its applications
TL;DR: In this paper, Spectral Analysis and its Applications, the authors present a set of applications of spectral analysis and its application in the field of spectroscopy, including the following:
Book
The Statistical Analysis of Time Series
TL;DR: The Wiley Classics Library as discussed by the authors is a collection of books that have become recognized classics in their respective fields, including some of the most important works of the 20th century in mathematics.
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The Modified Gauss-Newton Method for the Fitting of Non-Linear Regression Functions by Least Squares
TL;DR: The experimental scientist is frequently faced with the task of determining the functional relation between a response, y and a number of inputs, x, x2,. * *, x, with the help of empirical data.