-
Determines Hyperglycaemia Spreads in Generations with Multiple Complications That Imposing Towards Death
Sohani Afroja,
Masudul Islam,
Mohammad Emran Hossen,
Tapos Kumar Biswas
Issue:
Volume 3, Issue 2, March 2018
Pages:
16-23
Received:
23 May 2018
Accepted:
14 June 2018
Published:
13 July 2018
Abstract: Diabetes mellitus is one of the fast-growing global problems in the modern era. Khulna Division is not out of that. So, in this paper, it has been tried to recognize the multiple difficulties of hyperglycemia in Khulna, one of the divisions of Bangladesh. Branching process is obtained to determine the probability of ultimate extinction of hyperglycemia in generations. Bivariate and hierarchical multiple logistic regression models are used to examine the association of the determinants and hyperglycemia. Poisson regression is used to look at the number of multiple complications for forthcoming death. The place of resident, marital status, diabetes symptoms: nausea, diabetes symptoms: frequent previous generation and treatment gap are identified most significantly associate with the occurrence of hyperglycemia. Also, nausea person has further chance to attain a hyperglycemia as compared to non-nausea peoples in addition to male patients, if all other factors are constant. Also, the probability of extinction expresses zero for the people with diabetes and the tree diagram exhibits swiftness in the generation to generation. Overall, mortality risk factors among the people with diabetes for numerous worries are estimated by Poisson regression and try to avoid widespread of hyperglycemia in Khulna by diminishing the community health problem of diabetes.
Abstract: Diabetes mellitus is one of the fast-growing global problems in the modern era. Khulna Division is not out of that. So, in this paper, it has been tried to recognize the multiple difficulties of hyperglycemia in Khulna, one of the divisions of Bangladesh. Branching process is obtained to determine the probability of ultimate extinction of hyperglyc...
Show More
-
Monthly Forecasting of the Dollar to the Ruble Exchange Rate with Adaptive Kalman Filter
Issue:
Volume 3, Issue 2, March 2018
Pages:
24-29
Received:
1 June 2018
Accepted:
19 June 2018
Published:
13 July 2018
Abstract: The goal: to develop a model that allows you to forecast the dollar to the ruble exchange rate for a month ahead based on macroeconomic data, published at monthly intervals. Proposed structural model of the dynamics of the ruble and dollar masses that determine the exchange rate, depending on changes in foreign exchange reserves, the balance of foreign trade, the monetary base, the MICEX index, the price of oil. With the help of the Kalman filter (KF), the model parameters, the dynamics of the money masses were estimated, and forecasting of the dollar exchange rate was done. Monthly data were used from the beginning of 2015 to mid-2017. The estimation of the capacity of dollar market was found in about half the capacity of the MICEX index funds. Average error of forecasts, based on information available one step before the forecasted moments (RMSEA) was 1.99. Adaptive form of KF was developed when, similarly to the EM algorithm, the phases of KF estimation in the window and minimization of average prediction error to determine the optimal estimates for the system model parameters in this moment are sequentially alternated. With this RMSEA became 1.39.
Abstract: The goal: to develop a model that allows you to forecast the dollar to the ruble exchange rate for a month ahead based on macroeconomic data, published at monthly intervals. Proposed structural model of the dynamics of the ruble and dollar masses that determine the exchange rate, depending on changes in foreign exchange reserves, the balance of for...
Show More
-
A Survival Analysis of Invasive Breast Cancer Patients with and Without in Situ Neoplasm
Karim Atashgar,
Ayeh Sheikhaliyan,
Mina Tajvidi
Issue:
Volume 3, Issue 2, March 2018
Pages:
30-36
Received:
7 June 2018
Accepted:
25 June 2018
Published:
17 July 2018
Abstract: In situ neoplasm (or Carcinoma in situ (CIS)) is expression of malignant epithelial cells. This flat lesion is referred to as ductal carcinoma in situ (DCIS) and lobular carcinoma in situ (LCIS). Considering neoplasm leads one to an effectiveness survival analysis compared to the case that neoplasm is not attended. The objective of this research is to analyze statistically survival of invasive breast cancer patients considering 1) with in situ neoplasm, and 2) without in situ neoplasm, and providing a comparative analysis. This study attempts to reveal that the both medical history (such as diabetes, hypertension, and internal glands disorders such as hypo- and hyperthyroidism) and extra capsular extension play important roles in the hazard function of a patient’s survival analysis. This statistical study indicates that 1) the survival rate of breast cancer patients with in situ neoplasm is more than one who is not initially supported by invasive carcinoma, and 2) in the case of existence of the both in situ neoplasm and invasive malignancy, after the 4th year, the life expectancy is increased compared to the one with only invasive malignant. The statistical analysis indicates that pathology type is recognized as a high hazard factor for a breast cancer patient.
Abstract: In situ neoplasm (or Carcinoma in situ (CIS)) is expression of malignant epithelial cells. This flat lesion is referred to as ductal carcinoma in situ (DCIS) and lobular carcinoma in situ (LCIS). Considering neoplasm leads one to an effectiveness survival analysis compared to the case that neoplasm is not attended. The objective of this research is...
Show More
-
Efficiency Comparisons of Different Estimators for Panel Data Models with Serially Correlated Errors: A Stochastic Parameter Regression Approach
Issue:
Volume 3, Issue 2, March 2018
Pages:
37-51
Received:
5 June 2018
Accepted:
25 June 2018
Published:
25 July 2018
Abstract: This paper considers panel data models when the errors are first-order serially correlated as well as with stochastic regression parameters. The generalized least squares (GLS) estimators for these models have been derived and examined in this paper. Moreover, an alternative estimator for GLS estimators in small samples has been proposed, this estimator is called simple mean group (SMG). The efficiency comparisons for GLS and SMG estimators have been carried out. The Monte Carlo studies indicate that SMG estimator is more reliable in most situations than the GLS estimators, especially when the model includes one or more non-stochastic parameter.
Abstract: This paper considers panel data models when the errors are first-order serially correlated as well as with stochastic regression parameters. The generalized least squares (GLS) estimators for these models have been derived and examined in this paper. Moreover, an alternative estimator for GLS estimators in small samples has been proposed, this esti...
Show More
-
Suggestion a Novel Scenario in Iran Renewable Energy Planning Based on Modified ANN Method
Reza Gerami,
Morteza Mohammadi Ardehal
Issue:
Volume 3, Issue 2, March 2018
Pages:
52-61
Received:
7 June 2018
Accepted:
3 July 2018
Published:
27 July 2018
Abstract: In this study end-users energy consumption of Iran are predicted using ANN (artificial neural network) by historical data and socio-economic parameters (1990-2013) up to 2030 horizon. Iran energy balances are forecasted by bottom up analysis using LEAP (long-range energy alternative planning). On other hand solar energy promotion policies around the world, Iran policies and its solar energy potentials are investigated. Novel policy for Iran photovoltaic systems promotion are proposed and impact of this scenario implementation evaluated on Iran energy balance. Result show 750 MBOE (million barrel of oil equivalents) will be saved and 320 million metric tons co2 equivalent emission reduced up to 2030.
Abstract: In this study end-users energy consumption of Iran are predicted using ANN (artificial neural network) by historical data and socio-economic parameters (1990-2013) up to 2030 horizon. Iran energy balances are forecasted by bottom up analysis using LEAP (long-range energy alternative planning). On other hand solar energy promotion policies around th...
Show More
