Results 211 to 220 of about 2,912,658 (259)

Firm Size Distribution in Small Samples

Bulletin of Economic Research, 2004
AbstractSutton (1998) has recently proposed a theoretical lower bound to firm size inequality when a market is made of several independent submarkets. His results are valid asymptotically, as the number of submarkets becomes arbitrarily large. We show that, in small samples, his results can be interpreted as a positive relationship between an index of ...
BUZZACCHI, LUIGI, TOMMASO VALLETTI
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Small Sample Size Performance of the Energy Detector

IEEE Communications Letters, 2013
We examine the small sample size performance of the energy detector for spectrum sensing in AWGN. By making use of the cube-of-Gaussian approximation of chi-squared random variables, we derive a novel, simple, and accurate analytical expression for the minimum number of samples required to achieve a desired probability of detection and false alarm ...
RUGINI, LUCA, BANELLI, Paolo, G. Leus
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Exploratory Factor Analysis With Small Sample Sizes

Multivariate Behavioral Research, 2009
Exploratory factor analysis (EFA) is generally regarded as a technique for large sample sizes (N), with N = 50 as a reasonable absolute minimum. This study offers a comprehensive overview of the conditions in which EFA can yield good quality results for N below 50.
J C F, de Winter, D, Dodou, P A, Wieringa   +2 more
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Population Pharmacokinetics with a Very Small Sample Size

Drug Metabolism and Drug Interactions, 2009
The objective of this study was to evaluate whether pharmacokinetic parameters (clearance and volume of distribution of the central compartment) from a sparse sampling population pharmacokinetic study can be obtained with a very small sample size. For this study, three drugs were selected from the literature.
Iftekhar, Mahmood, John, Duan
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Stabilizing classifiers for very small sample sizes

Proceedings of 13th International Conference on Pattern Recognition, 1996
In this paper the possibilities for constructing linear classifiers are considered for very small sample sizes. We propose a stability measure and present a study on the performance and stability of the following techniques: regularization by the ridge-estimate of the covariance matrix, bootstrapping followed by aggregation ("bagging") and editing ...
Marina Skurichina, Robert P. W. Duin
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Solving the small sample size problem of LDA

Object recognition supported by user interaction for service robots, 2003
The small sample size problem is often encountered in pattern recognition. It results in the singularity of the within-class scattering matrix S/sub w/ in linear discriminant analysis (LDA). Different methods have been proposed to solve this problem in face recognition literature. Some methods reduce the dimension of the original sample space and hence
Rui Huang 0001, Qingshan Liu 0001, Hanqing Lu, Songde Ma   +3 more
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SMALL SAMPLE SIZE SCIENTIST

Pediatrics, 1989
The believer in the law of small numbers practices science as follows: 1. He gambles his research hypotheses on small samples without realizing that the odds against him are unreasonably high. He overestimates power. 2. He has undue confidence in early trends (e.g., the data of the first few subjects) and in the stability ...
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An Adjustment to the Bartlett's Test for Small Sample Size

Communications in Statistics - Simulation and Computation, 2014
The Bartlett's test (1937) for equality of variances is based on the χ2 distribution approximation. This approximation deteriorates either when the sample size is small (particularly < 4) or when the population number is large. According to a simulation investigation, we find a similar varying trend for the mean differences between empirical ...
Xiaobing Ma 0001, Feng-Chun Lin, Yu Zhao 0003   +2 more
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Sample Size Tables for Bounding Small Proportions

Biometrics, 1986
SUMMARY Sample size tables are given to be utilized in designing a study to provide an upper confidence bound for a small binomial proportion.
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Retrieving albedo in small sample size

IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings. (Cat. No.98CH36174), 1998
A new criteria for kernels' selection in Ambrals model is provided. Instead of using "least square" methods, "least variance" of white albedo which derived from Tarantola's information theory is used. Several tests showed "least variance" had many advantages. First, it is less sensitive to noise. Second, it operated well with a small sample size. Third,
null Feng Gao, A.H. Strahler, W. Lucht, null Zong-Guo Xia, null Xiaowen Li   +4 more
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