Intuitive statistical inference: How pigeons categorize binomial samples

Statistical Inference for the Lomax Distribution under Progressively Type-II Censoring with Binomial Removal

This paper considers parameter estimations in Lomax distribution under progressive type-II censoring with random removals, assuming that the number of units removed at each failure time has a binomial distribution. The maximum likelihood estimators (MLEs) are derived using the expectation-maximization (EM) algorithm. The Bayes estimates of the parameters are obtained using both the squared erro...

Procrustean statistical inference of deformations

A two step method has been devised for the statistical inference of deformation changes. In the first step of this method and based on Procrustes analysis of deformation tensors, the significance of the change in a time or space series of deformation tensors is statistically analyzed. In the second step significant change(s) in deformations are localized. In other words, they are assigned to ce...

Statistical inference for network samples using subgraph counts

We consider that a network is an observation, and a collection of observed networks forms a sample. In this setting, we provide methods to test whether all observations in a network sample are drawn from a specified model. We achieve this by deriving, under the null of the graphon model, the joint asymptotic properties of average subgraph counts as the number of observed networks increases but ...

Statistical inference for testing inequality indices with dependent samples

This paper develops asymptotically distribution-free inference for testing inequality indices with dependent samples. It considers the interpolated Gini coe$cient and the generalized entropy class, which includes several commonly used inequality indices. We "rst establish inference tests for changes in inequality indices with completely dependent samples (i.e., matched pairs) and then generaliz...

RUNNNING HEAD: Pigeons Attend to Features of Human Faces Pigeons and People Categorize Human Faces Using Similar Features