The aim of this article is two fold. First we discuss the maximum likelihood estimators of the unknown parameters of a two-parameter Birnbaum-Saunders distribution when the data are progressively Type-II censored. The maximum likelihood estimators are obtained using the EM algorithm by exploiting the property that the BirnbaumSaunders distribution can be expressed as an equal mixture of an inve...

Prediction on the basis of censored data is very important topic in many fields including medical and engineering sciences. In this paper, based on progressive Type-II right censoring scheme, we will discuss Bayesian two-sample prediction. A general form for lifetime model including some well known and useful models such asWeibull and Pareto is considered for obtaining prediction bounds ...

Consider critical percolation on a rhombus in the hexagonal lattice, and let A the event of a left to right crossing (by 1’s). Suppose we sample configurations from A by starting from some fixed configuration in A, and then at each step a uniformly random hexagon is resampled as long as the resulting configuration is in A. It is easy to see that this sampling procedure converges to the uniform ...

Multinomial Choice: Data consists of consumer choices of various goods, along char­ acteristics. Let there be J choices and y = (y1, . . . , yJ ) where yj = 1 if good j is chosen and yj = 0 otherwise. Let x be observed characteristics of the goods and choices. Here a conditional density for y corresponds to conditional choice probabilities P (j|x, β), one for each j, with �J j=1 P (j|x, β) = 1 ...

Identification in censored regression analysis and hazard models of duration outcomes relies on the condition that censoring points are independent of latent outcomes, an assumption which may be questionable in many settings. This note proposes a test for this assumption based on a Kolmogorov-Smirnov-like test statistic comparing two different nonparametric estimators for the latent outcome cdf...

When a spatial pattern is observed through a bounded window, inference about the pattern is hampered by sampling eeects known as \edge eeects". This chapter identiies two main types of edge eeects: size-dependent sampling bias and censoring eeects. Sampling bias can be eliminated by changing the sampling technique, or`corrected' by weighting the observations. Censoring eeects can be tackled usi...

Artificial neural networks are a powerful tool for analyzing data sets where there are complicated nonlinear interactions between the measured inputs and the quantity to be predicted. We show that the results obtained when neural networks are applied to survival data depend critically on the treatment of censoring in the data. When the censoring is modeled correctly, neural networks are a robus...

In this paper, we estimate the sensitivity of the adaptive censoring algorithm towards the change of the input parameters of pulse jamming of an Adaptive Postdetection Integration (API) CFAR processor. The censoring algorithm estimates the background environment and automatically defines the scale factor. We propose this algorithm to be used for the estimation of both, the probability of appear...