Specifying Weights in Spatial Forecasting Models: The Results of Some Experiments

1982 ◽  
Vol 14 (5) ◽  
pp. 571-584 ◽  
Author(s):  
F Stetzer
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Weight Function ◽  
Effective Area ◽  
Space Time ◽  
Distance Decay ◽  
Model Parameters ◽  
Sample Sizes ◽  
Forecasting Models ◽  
Estimation Of Model Parameters

The application of space-time forecasting models requires the specification of a set of place-to-place weights. The existing literature contains several recommendations for this specification. By a series of Monte Carlo simulations, various weighting rules are compared in terms of estimation of model parameters and accuracy of forecasts. It is shown that specification of the weights is important, especially when sample sizes are small and the data autocorrelated. Generally, the effective area of the weight function is more important than its distance decay.

scholarly journals TARANIS XGRE and IDEE Detection Capability of Terrestrial Gamma-Ray Flashes and Associated Electron Beams

2017 ◽  
Author(s):  
David Sarria ◽  
Francois Lebrun ◽  
Pierre-Louis Blelly ◽  
Remi Chipaux ◽  
Philippe Laurent ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Energy Range ◽  
Gamma Rays ◽  
Gamma Ray ◽  
Electron Beams ◽  
Effective Area ◽  
Detection Rates ◽  
Transient Phenomena ◽  
Preliminary Model

Abstract. With a launch expected in 2018, the TARANIS micro-satellite is dedicated to the study of transient phenomena observed in association with thunderstorms. On-board the spacecraft, XGRE and IDEE are two instruments dedicated to study Terrestrial Gamma-ray Flashes (TGFs) and associated electron beams (TEBs). XGRE can detect electrons (energy range: 1 MeV to 10 MeV) and X/gamma-rays (energy range: 20 keV to 10 MeV), with a very high counting capability (about 10 million counts per second), and the ability to discriminate one type of particle from the other. The IDEE instrument is focused on electrons in the 80 keV to 4 MeV energy range, with the ability to estimate their pitch angles. Monte-Carlo simulations of the TARANIS instruments, using a preliminary model of the spacecraft, allow sensitive area estimates for both instruments. It leads to an averaged effective area of 425 cm2 for XGRE to detect X/gamma rays from TGFs, and the combination of XGRE and IDEE gives an average effective area of 255 cm2 to detect electrons/positrons from TEBs. We then compare these performances to RHESSI, AGILE, and Fermi GBM, using performances extracted from literature for the TGF case, and with the help of Monte-Carlo simulations of their mass models for the TEB case. Combining these data with with the help of the MC-PEPTITA Monte-Carlo simulations of TGF propagation in the atmosphere, we build a self-consistent model of the TGF and TEB detection rates of RHESSI, AGILE, and Fermi. It can then be used to estimate that TARANIS should detect about 225 TGFs/year and 25 TEBs/year.

scholarly journals Performance of the Beta-Binomial Model for Clustered Binary Responses: Comparison with Generalized Estimating Equations

2021 ◽  
Vol 19 (1) ◽  
pp. 2-25
Author(s):  
Seongah Im
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Generalized Estimating Equations ◽  
Estimating Equations ◽  
Small Sample ◽  
Binomial Model ◽  
Sample Sizes ◽  
Binary Responses ◽  
Large Sample ◽  
Generalized Estimating

This study examined performance of the beta-binomial model in comparison with GEE using clustered binary responses resulting in non-normal outcomes. Monte Carlo simulations were performed under varying intracluster correlations and sample sizes. The results showed that the beta-binomial model performed better for small sample, while GEE performed well under large sample.

scholarly journals A new sewage exfiltration model – parameters and calibration

2011 ◽  
Vol 63 (10) ◽  
pp. 2294-2299 ◽  
Author(s):  
Christian Karpf ◽  
Peter Krebs
Keyword(s):  
Waste Water ◽  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Experimental Studies ◽  
Model Parameters ◽  
Potential Danger ◽  
Detailed Consideration ◽  
Sewer Systems ◽  
The Law ◽  
Groundwater Infiltration

Exfiltration of waste water from sewer systems represents a potential danger for the soil and the aquifer. Common models, which are used to describe the exfiltration process, are based on the law of Darcy, extended by a more or less detailed consideration of the expansion of leaks, the characteristics of the soil and the colmation layer. But, due to the complexity of the exfiltration process, the calibration of these models includes a significant uncertainty. In this paper, a new exfiltration approach is introduced, which implements the dynamics of the clogging process and the structural conditions near sewer leaks. The calibration is realised according to experimental studies and analysis of groundwater infiltration to sewers. Furthermore, exfiltration rates and the sensitivity of the approach are estimated and evaluated, respectively, by Monte-Carlo simulations.

SIMULATIONS OF GLYCOLYTIC OSCILLATIONS IN CELLS WITH COMPARTMENTS

2002 ◽  
Vol 12 (07) ◽  
pp. 1643-1652 ◽  
Author(s):  
VLADIMIR P. ZHDANOV
Keyword(s):  
Monte Carlo ◽  
Cell Membrane ◽  
Monte Carlo Simulations ◽  
Cell Size ◽  
Elementary Reaction ◽  
Model Parameters ◽  
Typical Size ◽  
Glycolytic Oscillations ◽  
Glucose Supply ◽  
In Cells

We present Monte Carlo simulations of glycolytic oscillations inside the cell with a chemically inactive compartment. The model employed takes into account the glucose supply to the cell via the cell membrane and a few elementary reaction steps running inside the cell in the area between the external membrane and the compartment. The model parameters are chosen so that the typical size of oscillatory patterns is comparable with the cell size. Although the compartment does not directly participate in the reaction, its presence is found to amplify irregular oscillations provided that the compartment size is appreciable and it is located in the center of the cell.

scholarly journals Uncertainty analysis of rising sewer models with respect to input parameters and model structure using Monte Carlo simulations and computational fluid dynamics

2021 ◽  
Author(s):  
Ahmed Khalil ◽  
Domenico Santoro ◽  
Damien J. Batstone ◽  
Christopher T. DeGroot
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Model Parameters ◽  
Model Structure ◽  
Mathematical Form ◽  
Homogeneous Surface ◽  
Simple Flows ◽  
D Model

Abstract Modelling conversion processes in sewers can help minimize odour and pipe corrosion issues, but model uncertainties and errors must be understood. In this study, the Wastewater Aerobic/Anaerobic Transformation in Sewers (WATS) model is implemented in two different frameworks; 1-D (CSTR-in-series) and computational fluid dynamics (CFD) to study the uncertainties due to model parameters and its mathematical form. The 1-D model is used to conduct uncertainty/sensitivity analysis using Monte Carlo simulations. Time-averaged outputs were represented using a general linearized model to quantify the importance of specific parameters. The sulfide formation rate per unit area of the biofilm is the most influential parameter. Parameters controlling anaerobic hydrolysis and fermentation are also significant. Uncertainty due to model structure is studied using CFD to explore the influences of non-homogeneous surface reactions and solids settling. These showed that the 1-D model provides a reasonable characterisation of the process for simple flows in pressure mains.

scholarly journals Impact of model parameters on Monte Carlo simulations of backscattering Mueller matrix images of colon tissue

2011 ◽  
Vol 2 (7) ◽  
pp. 1836 ◽  
Author(s):  
Maria-Rosaria Antonelli ◽  
Angelo Pierangelo ◽  
Tatiana Novikova ◽  
Pierre Validire ◽  
Abdelali Benali ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Mueller Matrix ◽  
Model Parameters ◽  
Colon Tissue

Analyzing the Robustness of Semi-Parametric Duration Models for the Study of Repeated Events

2014 ◽  
Vol 22 (2) ◽  
pp. 183-204 ◽  
Author(s):  
Janet M. Box-Steffensmeier ◽  
Suzanna Linn ◽  
Corwin D. Smidt
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Time Dependence ◽  
Frailty Model ◽  
Duration Models ◽  
Sample Sizes ◽  
Know How ◽  
Data Limitations ◽  
Repeated Events ◽  
Event Dependence

Estimators within the Cox family are often used to estimate models for repeated events. Yet, there is much we still do not know about the performance of these estimators. In particular, we do not know how they perform given time dependence, different censoring rates, and a varying number of events and sample sizes. We use Monte Carlo simulations to demonstrate the performance of a variety of popular semi-parametric estimators as these data aspects change and under conditions of event dependence and heterogeneity, both, or neither. We conclude that the conditional frailty model outperforms other standard estimators under a wide array of data-generating processes, and data limitations rarely alter its performance.

scholarly journals Estimation and inference of threshold regression models with measurement errors

2017 ◽  
Vol 22 (2) ◽  
Author(s):  
Terence Tai-Leung Chong ◽  
Haiqiang Chen ◽  
Tsz-Nga Wong ◽  
Isabel Kit-Ming Yan
Keyword(s):  
Monte Carlo ◽  
Measurement Errors ◽  
Regression Models ◽  
Estimation Method ◽  
Model Parameters ◽  
Threshold Regression ◽  
Coefficient Estimates ◽  
Consistent Estimation ◽  
Type Test ◽  
Estimation Of Model Parameters

Abstract An important assumption underlying standard threshold regression models and their variants in the extant literature is that the threshold variable is perfectly measured. Such an assumption is crucial for consistent estimation of model parameters. This paper provides the first theoretical framework for the estimation and inference of threshold regression models with measurement errors. A new estimation method that reduces the bias of the coefficient estimates and a Hausman-type test to detect the presence of measurement errors are proposed. Monte Carlo evidence is provided and an empirical application is given.

scholarly journals A software tool to assess uncertainty in transient-storage model parameters using Monte Carlo simulations

2017 ◽  
Vol 36 (1) ◽  
pp. 195-217 ◽  
Author(s):  
Adam S. Ward ◽  
Christa A. Kelleher ◽  
Seth J. K. Mason ◽  
Thorsten Wagener ◽  
Neil McIntyre ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Software Tool ◽  
Transient Storage ◽  
Model Parameters ◽  
Storage Model ◽  
Transient Storage Model
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