Distribution-Free Interval Estimation of the Largest α-Quantile

1972 ◽  
Vol 67 (337) ◽  
pp. 196
Author(s):  
M. Haseeb Rizvi ◽  
K. M. Lal Saxena
Keyword(s):  
Interval Estimation ◽  
Distribution Free ◽  
Free Interval

A Short Table for Both the Sign Test and Estimation of the Median for Sample Sizes to 1,000

1965 ◽  
Vol 17 (3) ◽  
pp. 927-932
Author(s):  
William J. Mackinnon
Keyword(s):  
Sample Size ◽  
Interval Estimation ◽  
Sign Test ◽  
Sample Sizes ◽  
Distribution Free ◽  
Free Interval

A table enables the researcher to perform the sign test and distribution-free interval estimation of the median. By virtue of using the critical sample-size as entry and also providing instructions about the simple calculating required for some applications, the table combines shortness of format and breadth of applicability, encompassing 12 probability levels and sample sizes to 1,000.

Asymptotic Distribution Free Interval Estimation

Methodology ◽  
2008 ◽  
Vol 4 (1) ◽  
pp. 4-9 ◽  
Author(s):  
Donna L. Coffman ◽  
Alberto Maydeu-Olivares ◽  
Jaume Arnau
Keyword(s):  
Confidence Intervals ◽  
Intraclass Correlation ◽  
Interval Estimation ◽  
Point Estimate ◽  
Distribution Free ◽  
Free Interval ◽  
Distributional Assumptions ◽  
Asymptotically Distribution Free ◽  
Coverage Rates ◽  
Better Than

Abstract. Confidence intervals for the intraclass correlation coefficient (ICC) have been proposed under the assumption of multivariate normality. We propose confidence intervals which do not require distributional assumptions. We performed a simulation study to assess the coverage rates of normal theory (NT) and asymptotically distribution free (ADF) intervals. We found that the ADF intervals performed better than the NT intervals when kurtosis was greater than 4. When violations of distributional assumptions were not too severe, both the intervals performed about the same. The point estimate of the ICC was robust to distributional violations. We provide R code for computing the ADF confidence intervals for the ICC.

scholarly journals Distribution-free confidence intervals for measurement of effective bandwidth

2000 ◽  
Vol 37 (1) ◽  
pp. 224-235 ◽  
Author(s):  
László Györfi ◽  
András Rácz ◽  
Ken Duffy ◽  
John T. Lewis ◽  
Fergal Toomey
Keyword(s):  
Confidence Intervals ◽  
Interval Estimation ◽  
Effective Bandwidth ◽  
Distribution Free ◽  
Peak Rate ◽  
Estimation Procedures ◽  
Hoeffding’S Inequality ◽  
Traffic Source

Hoeffding's inequality can be used in conjunction with the declared parameters of a traffic source, such as its peak rate, to obtain confidence intervals for measurements of the traffic's effective bandwidth. We describe a variety of interval-estimation procedures based on this idea, designed to provide differing degrees of robustness against non-stationarity. We also discuss how to compute confidence intervals for the effective bandwidth of an aggregate of traffic sources.

A Distribution Free Interval Estimate for Coefficient Alpha

2018 ◽  
Vol 25 (6) ◽  
pp. 876-887 ◽  
Author(s):  
Laura Trinchera ◽  
Nicolas Marie ◽  
George A. Marcoulides
Keyword(s):  
Coefficient Alpha ◽  
Interval Estimate ◽  
Distribution Free ◽  
Free Interval
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