Parameter variability and distributional assumptions in the diffusion model.

Psychological Review Parameter Variability and Distributional Assumptions in the Diffusion Model

Unfalsifiability and mutual translatability of major modeling schemes for choice reaction time.

[Correction Notice: An Erratum for this article was reported in Vol 121(1) of Psychological Review (see record 2014-03591-005). The link to supplemental material was missing. All versions of this article have been corrected.] Much current research on speeded choice utilizes models in which the response is triggered by a stochastic process crossing a deterministic threshold. This article focuses...

Monitoring process variability: a hybrid Taguchi loss and multiobjective genetic algorithm approach

The common consideration on economic model is that there is knowledge about the risk of occurrence of an assignable cause and the various cost parameters that does not always adequately describe what happens in practice. Hence, there is a need for more realistic assumptions to be incorporated. In order to reduce cost penalties for not knowing the true values of some parameters, this paper aims ...

Identification of the Best Infiltration Model in Order to Investigation of Spatial Variability of Infiltration Parameters (Case Study: Darabkola River Basin)

Infiltration is the process of water penetration from the ground surface into the soil and is an important process in the hydrological cycle by which surface runoff and groundwater recharge can be linked. Over the years, the importance of the infiltration process resulted in the development of several simplified analytical models for predicting infiltration. These infiltration models range from...

Bootstrap Prediction Intervals for Power-transformed Time Series

_________________________________________________________________ In this paper we propose a bootstrap resampling scheme to construct prediction intervals for future values of a variable after a linear ARIMA model has been fitted to a power transformation of it. The advantages over existing methods for computing prediction intervals of power transformed time series are that the proposed bootstr...