During the past 5 years there have been a number of important developments in the estimation of animal abundance and related parameters such as survival rates. Many of the new techniques need to be more widely publicized as they supplant previous methods. The aim of this paper is to review this literature and suggest further avenues for research.

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A review of estimating animal abundance.

In this article I review the modeling of capture, recapture, and removal statistics for the purpose of estimating demographic parameters of fish and wildlife populations. Topics considered include capture-recapture models, band or tag return models, removal and catch per unit effort models, selective removal or change-in-ratio models, radio-tagging survival models, and nest survival models. The purpose is to present important concepts in a general manner for the benefit of a wide audience of statisticians. I will not attempt to be comprehensive, and I indulge in speculation about future directions. I indicate the importance of different statistical tools to this subject, such as Bayesian inference, “boot strapping,” robustness studies, goodness-of-fit tests. I also emphasize connections to other application areas of statistics. Capture-recapture methods, for example, are being considered for estimation of a variety of elusive human populations, such as the homeless and people missed in the census...

Modeling capture, recapture, and removal statistics for estimation of demographic parameters for fish and wildlife populations : Past, present, and future

Benchmarking is recognised as an essential tool for continuous improvement of quality. A large number of publications by various authors reflect the interest in this technique. Reviews of literature on benchmarking have been done in the past by a few authors. However, considering the contributions in the recent times, a more comprehensive review is attempted here. In this paper, the authors have reviewed benchmarking literature in a way that would help researchers, academicians and practitioners to take a closer look at the growth, development and applicability of this technique. The authors have examined various papers and have proposed a different scheme of classification. In addition, certain gaps that would provide hints for further research in benchmarking have been identified.

A review of literature on benchmarking

The author identifies some of the persistent questions raised by people in education, business, and government who want to judge how well their texts are working. She compares the cognitive processes involved in reading to comprehend text with those involved in reading to evaluate and revise text, stressing that even experienced writers often need help in detecting and diagnosing text problems. She characterizes three general classes of tests for evaluating text quality: (1) text-focused, (2) expert-judgment-focused, and (3) reader-focused approaches. She reviews typical methods within each class, examining the strengths and limitations of particular tests, and discusses the relative advantages of reader-focused methods over other approaches. >

Evaluating text quality: the continuum from text-focused to reader-focused methods

http://romisatriawahono.net/lecture/rm/survey/network%20security/Li%20-%20Commercial%20Cloud%20Services%20-%202013.pdf

On evaluating commercial Cloud services

The practice of benchmarking as an assessment tool in computer performance evaluation is traced in this article from the early 1960s to the present. Included here are discussions of standard benchmark problems (used in Standard EDP Reports), application benchmarks, workload mapping, synthetic jobs, and the standard benchmark library concept. Advantages and disadvantages of the various techniques are given, along with a discussion of critical issues raised during the past two decades.

The evolution of benchmarking as a computer performance evaluation technique

SUMMARY Moran (1951) proposed an approximate formula for the likelihood of the size of an animal population when the 'removal method' is used. We here obtain an exact formula for the likelihood, based on an assumption of 'proportional trapping' of animals. The formula is ill conditioned and requires extremely high precision arithmetic for its numerical evaluation. A form of minimum chi-squared or weighted least-squares method is also given for estimating population size. For this method the calculations are not badly ill conditioned, and the method cuts down the work required for finding the maximum likelihood solution.

Byron C. Lewis

Papers

The evolution of benchmarking as a computer performance evaluation technique

Population estimation by the removal method assuming proportional trapping

A maximum-likelihood/minimum-discrepancy method for estimation of multinomial probabilities when there are related multinomials

The choice between techniques for choosing between methods of estimation

C304. A further note on probability estimation for pairs of related multinomials