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Showing 6 results for Simulation

Mm Maghami, Nasrollah Iranpanah,
Volume 13, Issue 3 (11-2013)
Abstract

There are several methods for goodness of fit test for the skew normal distribution. This work focused on method of Meintanis [8] which is based on the empirical moment generating function. This test is discussed for the known and the unknown shape parameter. Meintanis [8] claimed that power of his test is higher than the Kolmogorov–Smirnov test. But this claim is true only for the known shape parameter. In this paper, we provide a new method for finding his test statistic that has more efficiency. Also Meintanis [8] not determine the size of himself test for the known shape parameter which in this paper we will determine it.
Hamid Nassery, Rouhollah Adinehvand, Abdalrahim Salavitabar,
Volume 13, Issue 4 (2-2014)
Abstract

Tabriz plain with area of 869 square kilometers is a part of the Urmieh lake's catchment. The purpose of this study is to simulate the behavior of Tabriz aquifer against various stresses and determine the permissible level for the operation of the aquifer. To achieve the above objective the system dynamics simulation method has been used.
In this regard, the required information includes ground water resources data (wells, springs, qanat), sources and consumptions after analysis to eliminate defects was given to the VENSIM PLE+ software, and a dynamic simulation model was developed. Then by define the range of allowed water table fluctuations and the allocation of extracted water under these conditions, the allowable water level and safe yield of the aquifer was determined.
According to the obtained results in the six-year modeling period, the maximum amount of monthly and annual extraction without any damage from the aquifer is 12.70 and 152.45 million cubic meters respectively. The average of minimum and maximum allowable water table level during this period are 1317.35 and 1322.34 meters respectively.
Nasrollah Iranpanah, Samaneh Noori Emamzadeh,
Volume 14, Issue 2 (7-2014)
Abstract

Traditional methods for testing equality of means are based on normality observations in each treatment, but parametric bootstrap methods offer a test statistic to estimate P-value by resampling. In article, first, Fisher, Cochran, Welch, James, Brown and Forsyth, Approximate F, Weerahandi, Adjust Welch and Parametric Bootstrap tests for testing hypothesis equality of means are defined. Then type one error and power of these tests were compared to each other by a simulation study for various sizes of samples and treatments. Finally sizes of these tests were calculated for the real data of Esfahan Cement factory.
Traditional methods for testing equality of means are based on normality observations in each treatment, but parametric bootstrap methods offer a test statistic to estimate P-value by resampling. In article, first, Fisher, Cochran, Welch, James, Brown and Forsyth, Approximate F, Weerahandi, Adjust Welch and Parametric Bootstrap tests for testing hypothesis equality of means are defined. Then type one error and power of these tests were compared to each other by a simulation study for various sizes of samples and treatments. Finally sizes of these tests were calculated for the real data of Esfahan Cement factory.
Hamidreza Nassery, Zahra Kayhomayon, Mohammad Nakhaei,
Volume 16, Issue 42 (5-2015)
Abstract

The present study aimed at identifying the nitrate transport in the groundwater of Lenjanat plain, Isfahan. Nitrate concentrations were measured seasonally and groundwater flow was modeled for nitrate transport simulation using MODFLOW and MT3DMS codes. The nitrate concentrations were compared with the human and livestock drinking water and irrigation water standards. The results show that nitrate concentrations are higher than the guidelines limits in groundwaters. The flow modeling reveals that the groundwater flow system of the study aquifer has been influenced by the aquifer hydrogeological characteristics. The falling watertable and reduce aquifer storage are due to the anthropogenic stresses on flow system. The transport model calibration and sensitivity analysis shows that nitrate leaching from agricultural land, first–order irreversible rate reaction, effective porosity and precipitation are the major factors affecting the entry and retention of nitrate in Lenjanat groundwater. Denitrification rate in the aquifer has been decreased due to high concentration of dissolved oxygen in groundwater and low extent of organic carbon. Half-life of nitrate in Lenjanat aquifer is more than 2.5 years. Nitrate transport in the aquifer is mainly by convection. Considering the calculated mass with transport model, the nitrogen leaching to groundwater of study area is 108 kg N ha-1 yr-1.
Nasrollah Iranpanah, Parisa Mikelani,
Volume 17, Issue 40 (9-2015)
Abstract

One of the main goals in studying the time series is estimation of prediction interval based on an observed sample path of the process. In recent years, different semiparametric bootstrap methods have been proposed to find the prediction intervals without any assumption of error distribution. In semiparametric bootstrap methods, a linear process is approximated by a autoregressive process. Then the bootstrap samples are generated by resampling from the residuals.

In this paper, at first these sieve bootstrap methods are defined and then, in a simulation study sieve bootstrap prediction intervals are compared with a Standard Gaussian prediction interval. at last these methods are used to find the prediction intervals for weather data of Isfahan.
One of the main goals in studying the time series is estimation of prediction interval based on an observed sample path of the process. In recent years, different semiparametric bootstrap methods have been proposed to find the prediction intervals without any assumption of error distribution. In semiparametric bootstrap methods, a linear process is approximated by a autoregressive process. Then the bootstrap samples are generated by resampling from the residuals.

In this paper, at first these sieve bootstrap methods are defined and then, in a simulation study sieve bootstrap prediction intervals are compared with a Standard Gaussian prediction interval. at last these methods are used to find the prediction intervals for weather data of Isfahan.

Volume 18, Issue 48 (2-2007)
Abstract

Efron's bootstrap method can only be used to estimate the precision measures of estimators when observations are independent. For spatial data that are spatially correlated, the moving block bootstrap method is usually used. But, in this method, the boundary observations have less chance of presence in blocks resampling than the other observations. In this paper, the new separate block bootstrap method is introduced and an algorithm is given for estimating the precision measures of estimators. A simulation study is carried out to compare the efficiency of the separate block bootstrap method with moving block bootstrap. It is shown that, with their method we can estimate the bias of sample mean with no error, and the estimator for variance of sample mean is consistent.

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