A first‐order autoregressive process with one‐dimensional inverse Gaussian marginals is
introduced. The innovation distributions are obtained in certain special cases. The unknown …

A stationary sequence of random variables with Birnbaum‐Saunders marginal distribution is
constructed using a Gaussian autoregressive moving average sequence. The parameters of …

A bivariate semi-Pareto distribution is introduced and characterized using geometric
minimization. Autoregressive minification models for bivariate random vectors with bivariate …

This article proposes a first-order autoregressive model with Gumbel extreme value
marginal distribution to analyze the time-series data. As the innovation distribution of the …

MIMO systems using adaptive transmission down the eigenchannels require the level
crossing rate of the eigenvalues to compute adaptation rates and possibly feedback rates …

A unified formulation to generate branching processes with continuous or discrete state
space is provided. It includes processes with immigration and in varying environments. It …

This thesis develops the theory of continuous-time generalized AR (1) processes and
presents their use for non-normal time series models. The theory is of dual interest in …

The Markov sequences of non-negative random variables play important role in modelling
the time to events and time series. This chapter provides a detailed analysis of models …

Certified that the thesis entitled" SEQUENTIAL ESTIMATION IN SOME MARKOVIAN
MODELS" is a bonajide record ofwork done by Sri. TM Jacob under my guidance in the …

A first order autoregressive process with one-dimensional inverse Gaussian marginals is
introduced. The innovation distributions are obtained under certain special cases. The …