Effective and accurate reliability modeling requires the collection of comprehensive, homogeneous, and consistent data sets. Failure data required for software reliability modeling is difficult to collect, and even the available data tends to be noisy, distorted and unpredictable. Also, the complexity of the real world data might obscure the properties of the reliability models which are based ...

In [8] a new model validation method was proposed that is based on the estimation of an unbiased model of the model error which relates the inputs to the simulation errors. In this paper, we extend this methodology to closed-loop validation, i.e. the validation of an open-loop model on the basis of closed-loop validation data. We show that, perhaps surprisingly, the same model may fail to be va...

The primary objective of this paper is to revisit DSGE models with a view to appraise their statistical adequacy and propose ways to ameliorate their empirical pertinence. This paper brings out several weaknesses of the traditional DSGE modeling, including statistical misspecification, non-identification of deep parameters, substantive inadequacy, weak forecasting performance and potentially mi...

In this contribution we introduce a model quality measure called Modal Coherence Indicators which gives a complement to traditional model validation techniques. The indicators are derived by a geometric comparison of the model induced observability and controllability matrices with the data induced ones using a common description basis.

a robust linear quantitative structure-property relationship (qspr) model has been constructed to model and predict the refractivity indices of 101 organic compounds as common halo-derivatives of normal paraffin by application of the structural descriptors combined with multiple linear regression (mlr) method. in the main part of this study, theoretical molecular descriptors were adopted from t...

Abstract— Our increased dependence on computer models leads to the natural question – How do we increase the rigor in validating models against experimental data? Models have traditionally been tested against experimental data through simple comparisons such as x-y plots, scatter plots, or contour plots. While such qualitative comparisons are appropriate for model building, the use of such comp...

uniaxial compressive strength (ucs) is one of the most significant factors on the stability of underground excavation projects. most of the time, this factor can be obtained by exploratory boreholes evaluation. due to the large distance between exploratory boreholes in the majority of geotechnical projects, the application of geostatistical methods has increased as an estimator of rock mass pro...

hammerstein-wiener (hw) models are capable in describing nonlinear dynamic systems. these models are nonlinear and have been widely used in a wide range of sciences due to their simplicity and having a physically-based concept. in this research, for the first time in hydrology and water resources management, three different structures of these models using daily temperature and precipitation da...

reliable estimates of runoff are required as a part of the information sets that help watershed managers make informed decisions on water resources planning and management. this study was carried out in shafaroud watershed located in the north of iran. in order to achieve the best runoff simulation in the study area, first rainfall data of four stations during 1998 to 2011 were collected and co...

background: the present study was performed to develop a scoring system for predicting cure status in patients with cutaneous leishmaniasis (cl). materials and methods: this study included 199 patients with cl from skin diseases and leishmaniasis research center (isfahan, iran). data were collected as longitudinal in each visit of patients. we applied ordinal logistic generalized estimating equ...