Bayesian Modeling Method for an Observational Data Analysis

Bayesian propensity score analysis for observational data.

In the analysis of observational data, stratifying patients on the estimated propensity scores reduces confounding from measured variables. Confidence intervals for the treatment effect are typically calculated without acknowledging uncertainty in the estimated propensity scores, and intuitively this may yield inferences, which are falsely precise. In this paper, we describe a Bayesian method t...

Bayesian Prediction in Spatial Data Analysis

Data Envelopment Analysis with LINGO Modeling for Technical Educational Group of an Organization

Data Envelopment Analysis (DEA) was developed to help compare the relative performance of decision-making units. It is a non-parametric method for performing frontier analysis. It uses linear programming to estimate the efficiency of multiple decision-making units and it is commonly used in production, management and economics [3]. DEA generates an efficiency score between 0 and 1 for each unit...

an investigation about the appropriate stochastic modeling framework for agricultural insurance pricing

با توجه به اینکه بیمه محصولات کشاورزی در ایران بیشتر جنبه ای حمایتی دارد و خسارات گزارش شده عموما بیش از حق بیمه های دریافت شده است، در این پایان نامه به جهت تعیین قیمت بیمه محصولات کشاورزی (گندم دیم) از فرآیندهای نوفه شلیک به عنوان مدلی مناسب استفاده شده است. بر اساس داده های صندوق بیمه کشاورزی از خسارات اعلام شده در سال زراعی 1388-1389 گندم دیم، در این پایان نامه حق بیمه خالص و ناخالص این محص...

Bayesian Modeling Based on Data from the Internet of Things

The Internet of Things is suggested as the upcoming revolution in the Information and communication technology due to its very high capability of making various businesses and industries more productive and efficient. This productivity comes from the emergence of innovation and the introduction of new capabilities for businesses. Different industries have shown varying reactions to IOT, but wha...