1 |
HUGGINS, R. M. AND STAUDTE, R. G. (1994). 'Variance components models for dependent cell populations', Journal of the American Statistical Association, 89, 19-29
DOI
|
2 |
KLIMKO, L. A. AND NELSON, P. I. (1978). 'On conditional least squares estimation for stochastic processes', The Annals of Statistics, 6, 629-642
DOI
|
3 |
HWANG, S. Y. AND BASAWA, I. V. (2003). 'Estimation for nonlinear autoregressive models generated by beta-ARCH processes', Sankhya, 65, 744-762
|
4 |
BASAWA, I. V. AND ZHOU, J. (2004). 'Non-Gaussian bifurcating models and quasi-likelihood estimation', Journal of Applied Probability, 41A, 55-64
DOI
|
5 |
HWANG, S. Y. AND BASAWA, I. V. (1993). 'Asymptotic optimal inference for a class of nonlinear time series models', Stochastic Processes and Their Applications, 46, 91-113
DOI
ScienceOn
|
6 |
COWAN, R. AND STAUDTE, R. G. (1986). 'The bifurcating autoregression model in cell lineage studies', Biometrics, 42, 769-783
DOI
ScienceOn
|
7 |
HWANG, S. Y. AND BASAWA, I. V. (2006). 'Local asymptotic normality for bifurcating autoregressive processes and related asymptotic inference', Technical Report #2006-04, University of Georgia
|
8 |
ZHOU, J. AND BASAWA, I. V. (2005). 'Maximum likelihood estimation for first order bifurcating autoregressive process with exponential errors', Journal of Time Series Analysis, 26, 825-842
DOI
ScienceOn
|
9 |
FEIGIN, P. D. AND TWEEDIE, R. L. (1985). 'Random coefficient autoregressive processes: A Markov chain analysis of stationarity and finiteness of moments', Journal of Time Series Analysis, 6, 1-14
DOI
|
10 |
HALL, P. G. AND HEYDE, C. C. (1980). Martingale Limit Theory and Its Application, Academic Press, New York
|
11 |
GODAMBE, V. P. (1985). 'The foundations of finite sample estimation in stochastic processes', Biometrika, 72, 419-428
DOI
ScienceOn
|