Abstract
Abstract. In Nicholls and Quinn (1980) a procedure was proposed for the determination of strongly consistent estimates of random coefficient autoregressive models. These estimates are used here as starting values in a Newton‐Raphson algorithm which is employed to obtain the maximum likelihood estimates of a class of random coefficient autoregressions. The maximum likelihood estimates are shown to be strongly consistent and to satisfy a central limit theorem. The problem of testing for the randomness of the coefficients is also briefly discussed. The results of a number of simulations are reported which illustrate the theoretical results obtained.
Original language | English |
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Pages (from-to) | 185-203 |
Number of pages | 19 |
Journal | Journal of Time Series Analysis |
Volume | 2 |
Issue number | 3 |
DOIs | |
Publication status | Published - 1981 |
Externally published | Yes |
Keywords
- central limit theorem
- Maximum likelihood
- random coefficient autoregression
- stationarity
- strong consistency