Goodness-of-Fit Tests and Nonparametric Adaptive Estimation for Spike Train Analysis

Additional File 1 of ”Goodness-of-fit tests and non- parametric adaptive estimation for spike train analysis”: Kolmogorov-Smirnov tests, plug-in and sub-sampling

The Time-Rescaling Theorem and Its Application to Neural Spike Train Data Analysis

Measuring agreement between a statistical model and a spike train data series, that is, evaluating goodness of fit, is crucial for establishing the model's validity prior to using it to make inferences about a particular neural system. Assessing goodness-of-fit is a challenging problem for point process neural spike train models, especially for histogram-based models such as perstimulus time hi...

Three Papers by Peter Bickel on Nonparametric Curve Estimation

The following is a brief review of three landmark papers of Peter Bickel on theoretical and methodological aspects of nonparametric density and regression estimation and the related topic of goodness-of-fit testing, including a class of semiparametric goodness-of-fit tests. We consider the context of these papers, their contribution and their impact. Bickel’s first work on density estimation wa...

Capturing Spike Variability in Noisy Izhikevich Neurons Using Point Process Generalized Linear Models

To understand neural activity, two broad categories of models exist: statistical and dynamical. While statistical models possess rigorous methods for parameter estimation and goodness-of-fit assessment, dynamical models provide mechanistic insight. In general, these two categories of models are separately applied; understanding the relationships between these modeling approaches remains an area...

A New Goodness-of-Fit Test for a Distribution by the Empirical Characteristic Function

Extended Abstract. Suppose n i.i.d. observations, X1, …, Xn, are available from the unknown distribution F(.), goodness-of-fit tests refer to tests such as H0 : F(x) = F0(x) against H1 : F(x) $neq$ F0(x). Some nonparametric tests such as the Kolmogorov--Smirnov test, the Cramer-Von Mises test, the Anderson-Darling test and the Watson test have been suggested by comparing empirical ...