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Growth curve models with non‐stationary errors

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  • Eva Ferreira‐Garcıa
  • Vicente Núñez‐Antón
  • Juan Rodríguez‐Póo

Abstract

The estimation of growth curves has been extensively studied in both parametric and stationary situations. In this paper we propose the use of a transformation of the time scale that can produce non‐stationary covariance structure, with stationarity as a special case. First, we estimate the parameters of the covariance structure using nonlinear least squares, and with these estimators we estimate the average growth curve non‐parametrically. We conduct Monte Carlo studies to assess the influence of the number of subjects and the number of observations per subject on the estimation. © 1998 John Wiley & Sons, Ltd.

Suggested Citation

  • Eva Ferreira‐Garcıa & Vicente Núñez‐Antón & Juan Rodríguez‐Póo, 1997. "Growth curve models with non‐stationary errors," Applied Stochastic Models and Data Analysis, John Wiley & Sons, vol. 13(3‐4), pages 233-239, September.
    • Handle: RePEc:wly:apsmda:v:13:y:1997:i:3-4:p:233-239
    DOI: 10.1002/(SICI)1099-0747(199709/12)13:3/43.0.CO;2-B
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