Consider Wald's sequential probability ratio test for deciding whether a sequence of independent and identically distributed observations comes from a specified phase-type distribution or from an exponentially tilted alternative distribution. Exact decision boundaries for given type-I and type-II errors are derived by establishing a link with ruin theory. Information on the mean sample size of the test can be retrieved as well. The approach relies on the use of matrix-valued scale functions associated with a certain one-sided Markov additive process. By suitable transformations, the results also apply to other types of distributions, including some distributions with regularly varying tails
One way of handling composite hypotheses by SPRT's is to integrate out nuisance parameters under bot...
Let Xi be i.i.d. Xi∼Fθ. For some parametric families {Fθ}, we describe a monotonicity property of Ba...
A sequential Wald test for discrimination of two simple hypotheses θ = θ1 and θ = θ2 with boundaries...
Consider Wald's sequential probability ratio test for deciding whether a sequence of independent and...
In this thesis, we present an introduction to Wald’s Sequential Probability Ratio Test (SPRT) for bi...
The Wald's sequential probability ratio test (SPRT) of two simple hypotheses regarding the Lévy-Khin...
Sequential procedures of testing for structural stability do not provide enough guidance on the shap...
Sequential procedures of testing for structural stability do not provide enough guidance on the shap...
Consider the first order of autoregressive model $X\sb{n} = \theta + \rho X\sb{n-1} + \varepsilon\sb...
A sequential likelihood ratio test for Markov dependence in a sequence of observations is considered...
The sequential probability ratio test is an efficient test procedure compared to the fixed sample si...
Assume observations are from a subclass of a one parameter exponential family whose dominating measu...
We provide a recursive algorithm for determining the sampling plans of invariant Bayesian sequential...
The problem of robustifying of the sequential probability ratio test is considered for a discrete h...
In part I we derive a non-linear renewal theorem for random walks that are perturbed by an approxima...
One way of handling composite hypotheses by SPRT's is to integrate out nuisance parameters under bot...
Let Xi be i.i.d. Xi∼Fθ. For some parametric families {Fθ}, we describe a monotonicity property of Ba...
A sequential Wald test for discrimination of two simple hypotheses θ = θ1 and θ = θ2 with boundaries...
Consider Wald's sequential probability ratio test for deciding whether a sequence of independent and...
In this thesis, we present an introduction to Wald’s Sequential Probability Ratio Test (SPRT) for bi...
The Wald's sequential probability ratio test (SPRT) of two simple hypotheses regarding the Lévy-Khin...
Sequential procedures of testing for structural stability do not provide enough guidance on the shap...
Sequential procedures of testing for structural stability do not provide enough guidance on the shap...
Consider the first order of autoregressive model $X\sb{n} = \theta + \rho X\sb{n-1} + \varepsilon\sb...
A sequential likelihood ratio test for Markov dependence in a sequence of observations is considered...
The sequential probability ratio test is an efficient test procedure compared to the fixed sample si...
Assume observations are from a subclass of a one parameter exponential family whose dominating measu...
We provide a recursive algorithm for determining the sampling plans of invariant Bayesian sequential...
The problem of robustifying of the sequential probability ratio test is considered for a discrete h...
In part I we derive a non-linear renewal theorem for random walks that are perturbed by an approxima...
One way of handling composite hypotheses by SPRT's is to integrate out nuisance parameters under bot...
Let Xi be i.i.d. Xi∼Fθ. For some parametric families {Fθ}, we describe a monotonicity property of Ba...
A sequential Wald test for discrimination of two simple hypotheses θ = θ1 and θ = θ2 with boundaries...