Selection of Geotechnical Parameters Using the Statistics of Small Samples

2014 ◽  
Author(s):  
Jeffrey R. Keaton ◽  
Hari Ponnaboyina
Keyword(s):  
Small Samples ◽  
Geotechnical Parameters ◽  
Selection Of

DOES THIS SOUND FAMILIAR?

PEDIATRICS ◽  
1989 ◽  
Vol 83 (3) ◽  
pp. A78-A78
Author(s):  
Student
Keyword(s):  
Small Samples ◽  
The Law ◽  
Selection Of

A study of the statistical intuitions of experience research psychologists revealed a lingering belief in what may be called the "law of small numbers," according to which even small samples are highly representative of the populations from which they are drawn. The responses of these investigators reflected the expectation that a valid hypothesis about a population will be represented by a statistically significant result in a sample with little regard for its size. As a consequence researchers put too much faith in the results of small samples and grossly overestimated the replicability of such results. In the actual conduct of research, this bias leads to the selection of samples of inadequate size and to overinterpretation of findings.

A Modified Method to Fit Probability Distributions of Geotechnical Parameters Using Stochastic Weighted Entropy Principle

2014 ◽  
Vol 580-583 ◽  
pp. 9-16
Author(s):  
Shu Jun Zhang ◽  
Zhi Jun Xu ◽  
Luo Zhong ◽  
Zhao Ran Xiao
Keyword(s):  
Probability Distributions ◽  
Maximum Entropy Principle ◽  
Small Samples ◽  
Test Case ◽  
Geotechnical Parameters ◽  
Modified Method ◽  
Entropy Principle ◽  
Kolmogorov Smirnov ◽  
Engineering Significance

Due to various uncertainties, most of geotechnical parameters are small samples, which causes much trouble when the probability distribution of geotechnical parameter is fitted using traditional distributions. This paper uses stochastic weighted method to improve the small samples of Geotechnical parameters into big samples, thus solving the problems caused by the small samples. Meanwhile, the probability density function of geotechnical parameter is derived based on maximum entropy principle, the advantage of presented method is verified through Kolmogorov-Smirnov Test. Case study shows that the proposed method not only overcomes the dependence of conventional fitting methods on classical probability distributions, but also the fitting more close to the fact because the data come from the big sample improved by geotechnical parameters, which has important engineering significance.

scholarly journals Graphitization of Small Carbonate Samples for Paleoceanographic Research at the Godwin Radiocarbon Laboratory, University of Cambridge

Radiocarbon ◽  
2016 ◽  
Vol 58 (1) ◽  
pp. 89-97 ◽  
Author(s):  
E Freeman ◽  
L C Skinner ◽  
R Reimer ◽  
A Scrivner ◽  
S Fallon
Keyword(s):  
Iron Powder ◽  
Hydrogen Reduction ◽  
Ion Beam ◽  
Small Sample ◽  
Small Samples ◽  
University Of Cambridge ◽  
National University ◽  
Set Up ◽  
The University ◽  
Selection Of

AbstractA new radiocarbon preparation facility was set up in 2010 at the Godwin Laboratory for Palaeoclimate Research, at the University of Cambridge. Samples are graphitized via hydrogen reduction on an iron powder catalyst before being sent to the Chrono Centre, Belfast, or the Australian National University for accelerator mass spectrometry (AMS) analysis. The experimental setup and procedure have recently been developed to investigate the potential for running small samples of foraminiferal carbonate. By analyzing background values of samples ranging from 0.04 to 0.6 mg C along with similar sized secondary standards, the setup and experimental procedures were optimized for small samples. “Background” modern 14C contamination has been minimized through careful selection of iron powder, and graphitization has been optimized through the use of “small volume” reactors, allowing samples containing as little as 0.08 mg C to be graphitized and accurately dated. Graphitization efficiency/fractionation is found not to be the main limitation on the analysis of samples smaller than 0.07 mg C, which rather depends primarily on AMS ion beam optics, suggesting further improvements in small sample analysis might yet be achieved with our methodology.

scholarly journals Fitting Residual Error Structures for Growth Models in SAS PROC MCMC

2016 ◽  
Vol 77 (4) ◽  
pp. 587-612 ◽  
Author(s):  
Daniel McNeish
Keyword(s):  
Bayesian Methods ◽  
Variance Components ◽  
Applied Research ◽  
Growth Models ◽  
Residual Error ◽  
Small Samples ◽  
Standard Errors ◽  
Covariance Structures ◽  
Biased Estimates ◽  
Selection Of

In behavioral sciences broadly, estimating growth models with Bayesian methods is becoming increasingly common, especially to combat small samples common with longitudinal data. Although M plus is becoming an increasingly common program for applied research employing Bayesian methods, the limited selection of prior distributions for the elements of covariance structures makes more general software more advantages under certain conditions. However, as a disadvantage of general software’s software flexibility, few preprogrammed commands exist for specifying covariance structures. For instance, PROC MIXED has a few dozen such preprogrammed options, but when researchers divert to a Bayesian framework, software offer no such guidance and requires researchers to manually program these different structures, which is no small task. As such the literature has noted that empirical papers tend to simplify their covariance matrices to circumvent this difficulty, which is not desirable because such a simplification will likely lead to biased estimates of variance components and standard errors. To facilitate wider implementation of Bayesian growth models that properly model covariance structures, this article overviews how to generally program a growth model in SAS PROC MCMC and then demonstrates how to program common residual error structures. Full annotated SAS code and an applied example are provided.

scholarly journals The Chemical Preparation of AgCl for Measuring 36Cl in Polar Ice with Accelerator Mass Spectrometry

Radiocarbon ◽  
1986 ◽  
Vol 28 (2A) ◽  
pp. 556-560 ◽  
Author(s):  
N J Conard ◽  
David Elmore ◽  
P W Kubik ◽  
H E Gove ◽  
L E Tubbs ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Accelerator Mass Spectrometry ◽  
Chemical Separation ◽  
Small Samples ◽  
Metal Powders ◽  
Separation And Purification ◽  
Polar Ice ◽  
Yield Data ◽  
Glacial Ice ◽  
Selection Of

A method of chemical separation and purification of chloride from relatively small samples (500 to 2100g) of glacial ice is presented. With this procedure the first successful measurements of pre-bomb levels of 36Cl in Greenland ice have been made. Emphasis is placed on methods of reducing sulfur, which causes interference in the accelerator mass spectrometry, and in maximizing the yield. Data regarding the selection of materials for sample holders and the use of metal powders for extending the lifetime of the sample are also presented.

Oral Contraceptives and Psychiatric Disturbance: Evidence from Research

1973 ◽  
Vol 123 (576) ◽  
pp. 513-518 ◽  
Author(s):  
Myrna M. Weissman ◽  
Andrew E. Slaby
Keyword(s):  
Case Reports ◽  
Incidence Rates ◽  
Emotional Reactions ◽  
Small Samples ◽  
Psychiatric Disturbance ◽  
Double Blind ◽  
Contraceptive Agents ◽  
High Incidence ◽  
Lay Public ◽  
Selection Of

There is a commonly held conviction among physicians and the lay public that oral contraceptive agents are associated with a high incidence of adverse psychological effects, particularly depressive symptoms. This belief is enhanced by a body of literature which includes case reports, studies of small samples, and overall side effect incidence rates (1–22). Careful, adequately controlled, objective studies of emotional reactions are, however, lacking, and this can be ascribed to the serious problems inherent in the design of such studies. For example, adequate control groups are difficult to establish, and contraceptives cannot easily be randomly assigned. Studies using a placebo must also introduce other contraceptives; nonrandom processes operate in the selection of women for study. Suggestibility secondary to use of medication requires placebo double-blind studies in order to differentiate the psychological from the pharmacological effects.

scholarly journals An ‘in-production’ method for testing the sterility of infusion fluids

1975 ◽  
Vol 74 (1) ◽  
pp. 17-22 ◽  
Author(s):  
J. A. Rycroft ◽  
D. Moon
Keyword(s):  
Traditional Method ◽  
Production Method ◽  
Random Selection ◽  
Small Samples ◽  
Sterility Testing ◽  
Infusion Fluids ◽  
Selection Of

SUMMARYThe addition of dehydrated broth powder to a random selection of bottles from each batch of infusion fluids before sterilization, followed by incubation of the bottles after sterilization, provides a method of sterility testing which possesses many advantages over the traditional method of culturing small samples from bottles after sterilization.

scholarly journals Analysis Strategy for Assisted Selection of Rice Eating Quality by Using Starch Properties

2020 ◽  
Author(s):  
Xu Li ◽  
Ting Mao ◽  
Yu Wang ◽  
Xin Sui ◽  
Hai Ren ◽  
...  
Keyword(s):  
Sensory Evaluation ◽  
Amylose Content ◽  
Recombinant Inbred Lines ◽  
Small Samples ◽  
Test Material ◽  
Eating Quality ◽  
Milled Rice ◽  
Starch Properties ◽  
Sensory Evaluations ◽  
Selection Of

Abstract Background Eating quality is the main factor affecting the commodity value of commercial rice. However, its determination relies on sensory evaluations, which require large samples, are easily influenced by subjective factors and are time consuming. In order to make the determination of eating quality more efficient, a set of recombinant inbred lines (RILs) obtained from the hybridization of indica and japonica rice was used as the test material to analyze the relationship between starch characteristics and the eating quality (EQ) score, from sensory evaluation. An implementation protocol was proposed for starch assisted-selection of eating quality. Results Among the RILs, the values of the measured parameters for amylose content (AC), trough viscosity (TV), final viscosity (FV), breakdown (BD) and setback (SB) were significantly correlated with the EQ values ​​obtained by sensory evaluation. The RILs with higher EQ scores, generally had low AC, TV, FV and SB, but high BD. By normalizing and summing the AC, TV, FV, SB and BD indicators, a comprehensive indicator—viz., the starch properties quality (SPQ)—was established, to assess starch quality. The SPQ value was better correlated with EQ than any of the individually measured parameters, suggesting that the model is valid. This method requires much smaller rice samples than sensory evaluations, i.e., three grams of milled rice flour. Conclusions Therefore, the SPQ indicator is a rapid, objective and convenient technique for the rapid assessment of rice eating quality in a large number of crossbreeding progeny, especially early-generation progeny, from which only small samples of rice grains are available.

Parameter Selection of SVR Based on Improved K-Fold Cross Validation

2013 ◽  
Vol 462-463 ◽  
pp. 182-186 ◽  
Author(s):  
Ju E Wang ◽  
Jian Zhong Qiao
Keyword(s):  
Time Series ◽  
Cross Validation ◽  
Time Series Data ◽  
Parameter Selection ◽  
Small Samples ◽  
Series Data ◽  
Support Vector ◽  
Model Parameters ◽  
Fold Cross Validation ◽  
Selection Of

This article firstly uses svm to forecast cashmere price time series. The forecasting result mainly depends on parameter selection. The normal parameter selection is based on k-fold cross validation. The k-fold cross validation is suitable for classification. In this essay, k-fold cross validation is improved to ensure that only the older data can be used to forecast latter data to improve prediction accuracy. This essay trains the cashmere price time series data to build mathematical model based on SVM. The selection of the model parameters are based on improved cross validation. The price of Cashmere can be forecasted by the model. The simulation results show that support vector machine has higher fitting precision in the situation of small samples. It is feasible to forecast cashmere price based on SVM.

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