Generalized linear modeling approach to stochastic weather generators

A Generalized Linear Statistical Model Approach to Monitor Profiles

Statistical process control methods for monitoring processes with univariate ormultivariate measurements are used widely when the quality variables fit to known probabilitydistributions. Some processes, however, are better characterized by a profile or a function of qualityvariables. For each profile, it is assumed that a collection of data on the response variable along withthe values of the c...

Fast Generalized Stochastic Linear Bandit

We study a generalized stochastic linear bandit problem and propose an algorithm 1 that enjoys fast update. The computational complexity of the update is O(d), 2 where d is the dimension of a context space. In comparison with other stochastic 3 linear bandit algorithms, our algorithm does not need to incrementally update the 4 inverse of a matrix so that it can avoid the O(d) computations. Yet,...

Generalized Linear Modeling

Interpolation of signals by generalized piecewise-linear multiple generators

This paper presents an interpolation method based on shifted versions of two piecewise linear generators, which provides approximation order 2 like usual piecewise-linear interpolation; i.e., this method is able to represent the constant and the ramp exactly. Our interpolation is characterized by two real parameters: τ , the location of the generators, and α, related to their dissymmetry. By va...

From Stochastic Nonlinear Integrate-and-Fire to Generalized Linear Models

Variability in single neuron models is typically implemented either by a stochastic Leaky-Integrate-and-Fire model or by a model of the Generalized Linear Model (GLM) family. We use analytical and numerical methods to relate state-of-theart models from both schools of thought. First we find the analytical expressions relating the subthreshold voltage from the Adaptive Exponential Integrate-andF...