A confidence interval approach to data analysis

A Procedure for Building Confidence Interval on the Mean of Simulation Output Data

One of the existing methods to build a confidence interval (c.i.) for the mean response in a single steady state simulation system is the batch means method. This method, compared to the other existing methods (autoregressive representation, regenerative cycles, spectrum analysis, standardized time series), is quite easy to understand and to implement and performs relatively well. However, the ...

Confidence Interval Estimation of the Mean of Stationary Stochastic Processes: a Comparison of Batch Means and Weighted Batch Means Approach (TECHNICAL NOTE)

Suppose that we have one run of n observations of a stochastic process by means of computer simulation and would like to construct a condifence interval for the steady-state mean of the process. Seeking for independent observations, so that the classical statistical methods could be applied, we can divide the n observations into k batches of length m (n= k.m) or alternatively, transform the cor...

Statistical Topology Using the Nonparametric Density Estimation and Bootstrap Algorithm

This paper presents approximate confidence intervals for each function of parameters in a Banach space based on a bootstrap algorithm. We apply kernel density approach to estimate the persistence landscape. In addition, we evaluate the quality distribution function estimator of random variables using integrated mean square error (IMSE). The results of simulation studies show a significant impro...

Bayes Interval Estimation on the Parameters of the Weibull Distribution for Complete and Censored Tests

A method for constructing confidence intervals on parameters of a continuous probability distribution is developed in this paper. The objective is to present a model for an uncertainty represented by parameters of a probability density function.  As an application, confidence intervals for the two parameters of the Weibull distribution along with their joint confidence interval are derived. The...

Robust Optimization and Confidence Interval DEA for Efficiency Evaluation with Intervals Case Study: Evaluating CRM Units in a Call Center in Tehran

DEA Models with Interval Scale Inputs and Outputs

This paper proposes an alternative approach for efficiency analysis when a set of DMUs uses interval scale variables in the productive process. To test the influence of these variables, we present a general approach of deriving DEA models to deal with the variables. We investigate a number of performance measures with unrestricted-in-sign interval and/or interval scale variables.