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Journal articles on the topic 'Hypothesis sampling'

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Published: 10 December 2022

Last updated: 29 January 2023

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1

Givaruangsawat, Sumalee, Govinda J. Weerakkody, and Patrick D. Gerard. "Hypothesis Testing in Two-Stage Cluster Sampling." Australian New Zealand Journal of Statistics 40, no. 3 (September 1998): 335–44. http://dx.doi.org/10.1111/1467-842x.00037.

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2

Bernstein, Joseph, Kevin McGuire, and Kevin B. Freedman. "Statistical Sampling and Hypothesis Testing in Orthopaedic Research." Clinical Orthopaedics and Related Research 413 (August 2003): 55–62. http://dx.doi.org/10.1097/01.blo.0000079769.06654.8c.

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3

Paul, Jack W. "Explaining attributes-sampling concepts: A hypothesis-testing framework." Journal of Accounting Education 12, no. 1 (December 1994): 43–58. http://dx.doi.org/10.1016/0748-5751(94)90018-3.

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4

Perron, Pierre. "Test Consistency with Varying Sampling Frequency." Econometric Theory 7, no. 3 (September 1991): 341–68. http://dx.doi.org/10.1017/s0266466600004503.

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This paper considers the consistency property of some test statistics based on a time series of data. While the usual consistency criterion is based on keeping the sampling interval fixed, we let the sampling interval take any equispaced path as the sample size increases to infinity. We consider tests of the null hypotheses of the random walk and randomness against positive autocorrelation (stationary or explosive). We show that tests of the unit root hypothesis based on the first-order correlation coefficient of the original data are consistent as long as the span of the data is increasing. Tests of the same hypothesis based on the first-order correlation coefficient of the first-differenced data are consistent against stationary alternatives only if the span is increasing at a rate greater than T½, where T is the sample size. On the other hand, tests of the randomness hypothesis based on the first-order correlation coefficient applied to the original data are consistent as long as the span is not increasing too fast. We provide Monte Carlo evidence on the power, in finite samples, of the tests Studied allowing various combinations of span and sampling frequencies. It is found that the consistency properties summarize well the behavior of the power in finite samples. The power of tests for a unit root is more influenced by the span than the number of observations while tests of randomness are more powerful when a small sampling frequency is available.

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5

KNEZ, IGOR. "Interaction of data and hypotheses in probabilistic inference tasks: Rejection of the hypothesis sampling model?" Scandinavian Journal of Psychology 32, no. 1 (March 1991): 57–69. http://dx.doi.org/10.1111/j.1467-9450.1991.tb00853.x.

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6

Lifshits, Mikhail, and Michel Weber. "Sampling the Lindelöf Hypothesis with the Cauchy random walk." Proceedings of the London Mathematical Society 98, no. 1 (June 24, 2008): 241–70. http://dx.doi.org/10.1112/plms/pdn026.

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7

Bahr, R. K., and J. A. Bucklew. "Optimal sampling schemes for the Gaussian hypothesis testing problem." IEEE Transactions on Acoustics, Speech, and Signal Processing 38, no. 10 (1990): 1677–86. http://dx.doi.org/10.1109/29.60099.

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8

DWORIN, LOWELL, and RICHARD A. GRIMLUND. "A comprehensive hypothesis testing approach to dollar unit sampling." Contemporary Accounting Research 5, no. 2 (March 1989): 674–91. http://dx.doi.org/10.1111/j.1911-3846.1989.tb00733.x.

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9

Harrison, M. T. "Conservative hypothesis tests and confidence intervals using importance sampling." Biometrika 99, no. 1 (February 7, 2012): 57–69. http://dx.doi.org/10.1093/biomet/asr079.

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10

Arnoldsson, Göran. "OPTIMAL DESIGNS FOR BINOMIAL SAMPLING UNDER A MIXTURE HYPOTHESIS." Communications in Statistics - Theory and Methods 30, no. 5 (April 30, 2001): 897–911. http://dx.doi.org/10.1081/sta-100002265.

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11

Denison, Stephanie, Elizabeth Bonawitz, Alison Gopnik, and Thomas L. Griffiths. "Rational variability in children’s causal inferences: The Sampling Hypothesis." Cognition 126, no. 2 (February 2013): 285–300. http://dx.doi.org/10.1016/j.cognition.2012.10.010.

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12

Hochman, Guy, and Ido Erev. "The partial-reinforcement extinction effect and the contingent-sampling hypothesis." Psychonomic Bulletin & Review 20, no. 6 (April 18, 2013): 1336–42. http://dx.doi.org/10.3758/s13423-013-0432-1.

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13

Bentivegna, Marco, Nicolò Spagnolo, Chiara Vitelli, Daniel J. Brod, Andrea Crespi, Fulvio Flamini, Roberta Ramponi, et al. "Bayesian approach to Boson sampling validation." International Journal of Quantum Information 12, no. 07n08 (November 2014): 1560028. http://dx.doi.org/10.1142/s021974991560028x.

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The Boson sampling problem consists in sampling from the output probability distribution of a bosonic Fock state, after it evolves through a linear interferometer. There is strong evidence that Boson sampling is computationally hard for classical computers, while it can be solved naturally by bosons. This has led it to draw increasing attention as a possible way to provide experimental evidence for the quantum computational supremacy. Nevertheless, the very complexity of the problem makes it hard to exclude the hypothesis that the experimental data are sampled from a different probability distribution. By exploiting integrated quantum photonics, we have carried out a set of three-photon Boson sampling experiments and analyzed the results using a Bayesian approach, showing that it represents a valid alternative to currently used methods. We adopt this approach to provide evidence that the experimental data correspond to genuine three-photon interference, validating the results against fully and partially-distinguishable photon hypotheses.

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14

Asmussen, M. A., and C. J. Basten. "Sampling theory for cytonuclear disequilibria." Genetics 138, no. 4 (December 1, 1994): 1351–63. http://dx.doi.org/10.1093/genetics/138.4.1351.

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Abstract We examine the statistical properties of cytonuclear disequilibria within a system including one diploid nuclear locus and one haploid cytoplasmic locus, each with two alleles. The results provide practical guidelines for the design and interpretation of cytonuclear surveys seeking to utilize the novel evolutionary information recorded in the observed pattern of cytonuclear associations. Important applications include population studies of nuclear allozymes in conjunction with genes from mitochondria, chloroplasts, or cytoplasmically inherited microorganisms. Our attention focuses on the allelic and genotypic disequilibria, which respectively measure the nonrandom associations between the cytotypes and the nuclear alleles and genotypes. We first derive the maximum likelihood estimators and their approximate large sample variances for each disequilibrium measure. These are each in turn used to set up an asymptotic test of the null hypothesis of no disequilibrium. We then calculate the minimum sample sizes required to detect the disequilibria under specified alternate hypotheses. The work also incorporates the deviation from Hardy-Weinberg equilibrium at the nuclear locus, which can significantly affect the results. The practical utility of this new sampling theory is illustrated through applications to two nuclear-mitochondrial data sets.

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15

Kanji, Tanaka. "Incremental Loop Closure Verification by Guided Sampling." Journal of Advanced Computational Intelligence and Intelligent Informatics 21, no. 1 (January 20, 2017): 59–66. http://dx.doi.org/10.20965/jaciii.2017.p0059.

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Loop closure detection, which is the task of identifying locations revisited by a robot in a sequence of odometry and perceptual observations, is typically formulated as a combination of two subtasks: (1) bag-of-words image retrieval and (2) post-verification using random sample consensus (RANSAC) geometric verification. The main contribution of this study is the proposal of a novel post-verification framework that achieves good precision recall trade-off in loop closure detection. This study is motivated by the fact that not all loop closure hypotheses are equally plausible (e.g., owing to mutual consistency between loop closure constraints) and that if we have evidence that one hypothesis is more plausible than the others, then it should be verified more frequently. We demonstrate that the loop closure detection problem can be viewed as an instance of a multi-model hypothesize-and-verify framework. Thus, we can build guided sampling strategies on this framework where loop closures proposed using image retrieval are verified in a planned order (rather than in a conventional uniform order) to operate in a constant time. Experimental results using a stereo simultaneous localization and mapping (SLAM) system confirm that the proposed strategy, the use of loop closure constraints and robot trajectory hypotheses as a guide, achieves promising results despite the fact that there exists a significant number of false positive constraints and hypotheses.

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van de Wouw, Didrika S., Ryan T. McKay, Bruno B. Averbeck, and Nicholas Furl. "Explaining human sampling rates across different decision domains." Judgment and Decision Making 17, no. 3 (May 2022): 487–512. http://dx.doi.org/10.1017/s1930297500003557.

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AbstractUndersampling biases are common in the optimal stopping literature, especially for economic full choice problems. Among these kinds of number-based studies, the moments of the distribution of values that generates the options (i.e., the generating distribution) seem to influence participants’ sampling rate. However, a recent study reported an oversampling bias on a different kind of optimal stopping task: where participants chose potential romantic partners from images of faces (Furl et al., 2019). The authors hypothesised that this oversampling bias might be specific to mate choice. We preregistered this hypothesis and so, here, we test whether sampling rates across different image-based decision-making domains a) reflect different over- or undersampling biases, or b) depend on the moments of the generating distributions (as shown for economic number-based tasks). In two studies (N = 208 and N = 96), we found evidence against the preregistered hypothesis. Participants oversampled to the same degree across domains (compared to a Bayesian ideal observer model), while their sampling rates depended on the generating distribution mean and skewness in a similar way as number-based paradigms. Moreover, optimality model sampling to some extent depended on the the skewness of the generating distribution in a similar way to participants. We conclude that oversampling is not instigated by the mate choice domain and that sampling rate in image-based paradigms, like number-based paradigms, depends on the generating distribution.

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Wagner, Peter J. "Likelihood tests of hypothesized durations: determining and accommodating biasing factors." Paleobiology 26, no. 3 (2000): 431–49. http://dx.doi.org/10.1666/0094-8373(2000)026<0431:ltohdd>2.0.co;2.

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Paleobiologists frequently hypothesize that a taxon's duration (i.e., the true span from origination to extinction) exceeds its stratigraphic range (i.e., the span from first appearance to last appearance in the fossil record). One can test hypothesized duration by assessing the plausibility of the implicitly hypothesized gaps between origination and first appearance and / or between last appearance and extinction. Several tests assess the probability of not finding a taxon over some stratigraphic gap. Because the likelihood of a hypothesis given data reflects the probability of the data given that hypothesis, these probabilities also give the likelihood of a hypothesized duration. However, many probability / likelihood tests require simplifying assumptions about unknown sampling parameters such as the consistency of sampling over time, sampling intensities for unknown ancestors, and actual sampling intensities themselves.This paper examines the effects of sampling parameters on probability / likelihood tests and presents methods for testing hypotheses about these unknowns while testing hypotheses about true durations. Two data sets are used here as examples. One analysis tests the origination times among Paleozoic gastropods implied by phylogenetic inferences. The other analysis tests the extinction times among Maastrichtian ammonites implied by different numbers of extinction events. In both cases, hypotheses positing many gaps in the fossil record become more likely after accommodating uncertainty about sampling. However, the increased likelihoods are insufficient to prevent these hypotheses from being rejected in favor of hypotheses positing fewer gaps. In both cases, the conclusions are identical to those derived by simple methods using simple models for unknown sampling parameters. Although numerous factors can exaggerate the implausibility of gaps, making these factors parts of testable hypotheses is possible. Thus, excessive assumptions about sampling parameters need not hinder empirical testing of hypothesized durations.

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Aulia, Kiara Cindy, Ardianik, and Windi Setiawan. "PENERAPAN MODEL PEMBELAJARAN KOOPERATIF TERHADAP HASIL BELAJAR MATEMATIKA DITINJAU DARI TINGKAT MOTIVASI." Center Of Education Journal (CEJou) 3, no. 2 (September 26, 2022): 19–26. http://dx.doi.org/10.55757/cejou.v3i2.160.

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The purpose of this study was to determine the differences in various cooperative learning models such as the Jigsaw type, the STAD type, and the GI type. This research is a quasi-experimental research. The sample consisted of three classes, namely class 7A subjected to treatment I, class 7B was subjected to treatment II, and class 7C to treatment III, sampling was carried out using cluster sampling technique. Data collection techniques using the method of tests and questionnaires. The data analysis technique used Kruskal Wallis non-parametric statistics. The results of data analysis resulted in 5 different hypotheses. The first hypothesis is the value of Asym Sig. 0.000 < 0.05, the second hypothesis obtained the value of Asym Sig. 0.000 < 0.05, the third hypothesis obtained the Asym Sig value. 0.280 is greater than 0.05, the fourth hypothesis is obtained by the Asym Sig value. 0.000 is smaller than 0.05 and the last hypothesis is the Asym Sig value. 0.006 < 0.05.

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Nikitina, M. A., and I. M. Chernukna. "Methods for nonparametric statistics in scientific research. Overview. Part 1." Theory and practice of meat processing 6, no. 2 (July 29, 2021): 151–62. http://dx.doi.org/10.21323/2414-438x-2021-6-2-151-162.

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Daily, researcher faces the need to compare two or more observation groups obtained under different conditions in order to confirm or argue against a scientific hypothesis. At this stage, it is necessary to choose the right method for statistical analysis. If the statistical prerequisites are not met, it is advisable to choose nonparametric analysis. Statistical analysis consists of two stages: estimating model parameters and testing statistical hypotheses. After that, the interpretation of the mathematical processing results in the context of the research object is mandatory. The article provides an overview of two groups of nonparametric tests: 1) to identify differences in indicator distribution; 2) to assess shift reliability in the values of the studied indicator. The first group includes: 1) Rosenbaum Q-test, which is used to assess the differences by the level of any quantified indicator between two unrelated samplings; 2) Mann-Whitney U-test, which is required to test the statistical homogeneity hypothesis of two unrelated samplings, i. e. to assess the differences by the level of any quantified indicator between two samplings. The second group includes sign G-test and Wilcoxon T-test intended to determine the shift reliability of the related samplings, for example, when measuring the indicator in the same group of subjects before and after some exposure. Examples are given; step-by-step application of each test is described. The first part of the article describes simple nonparametric methods. The second part describes nonparametric tests for testing hypotheses of distribution type (Pearson’s chi-squared test, Kolmogorov test) and nonparametric tests for testing hypotheses of sampling homogeneity (Pearson’s chi-squared test for testing sampling homogeneity, Kolmogorov-Smirnov test).

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20

Hsieh, Ching-Ying, and Jen-Pei Liu. "An Approximate Approach to Sampling Size Determination for the Equivalence Hypothesis." Journal of Biopharmaceutical Statistics 23, no. 3 (April 23, 2013): 526–38. http://dx.doi.org/10.1080/10543406.2012.755995.

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21

Brkic, Dragoljub. "Application of the randomized test for verifying the random sampling hypothesis." Vojnotehnicki glasnik 50, no. 2 (2002): 208–14. http://dx.doi.org/10.5937/vojtehg0202208b.

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22

Coulibaly, N., and B. Wade Brorsen. "Monte carlo sampling approach to testing nonnested hypothesis: monte carlo results." Econometric Reviews 18, no. 2 (January 1999): 195–209. http://dx.doi.org/10.1080/07474939908800439.

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23

Mandjes, M., and L. Ravner. "Hypothesis testing for a Lévy-driven storage system by Poisson sampling." Stochastic Processes and their Applications 133 (March 2021): 41–73. http://dx.doi.org/10.1016/j.spa.2020.11.005.

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24

PORTEOUS, B. T. "The mutual independence hypothesis for categorical data in complex sampling schemes." Biometrika 74, no. 4 (1987): 857–62. http://dx.doi.org/10.1093/biomet/74.4.857.

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25

Karimi, Maryam, and Sayed Mohammad Reza Alavi. "The effect of weight function on hypothesis testing in weighted sampling." Journal of Applied Statistics 41, no. 11 (June 9, 2014): 2493–503. http://dx.doi.org/10.1080/02664763.2014.920777.

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26

Samohyl, Robert Wayne. "Acceptance sampling for attributes via hypothesis testing and the hypergeometric distribution." Journal of Industrial Engineering International 14, no. 2 (October 7, 2017): 395–414. http://dx.doi.org/10.1007/s40092-017-0231-9.

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27

Zacks, Shelemyahu. "Two-stage and sequential sampling for estimation and testing with prescribed precision." Encyclopedia with Semantic Computing and Robotic Intelligence 01, no. 01 (March 2017): 1650004. http://dx.doi.org/10.1142/s2425038416500048.

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Statistical data analysis includes several phases. First, there is the phase of data collection. Second, there is the phase of analysis and inference. The two phases are interconnected. There are two types of data analysis. One type is called parametric and the other type is nonparametric. In the present paper, we discuss parametric inference. In parametric inference, we model the results of a given experiment as realization of random variables having a particular distribution, which is specified by its parameters. A random sample is a sequence of independent and identically distributed (i.i.d.) random variables. Statistics are functions of the data in the sample, which do not involve unknown parameters. A statistical inference is based on statistics of a given sample. We discuss two kinds of parametric inference. Estimating the values of parameters, or testing hypotheses concerning the parameters in either kind of inference, we are concerned with the accuracy and precision of the results. In estimation of parameters, the results are precise if, with high probability, they belong to a specified neighborhoods of the parameters. In testing hypotheses, one has to decide which one of two or several hypotheses should be accepted. Hypotheses which are not accepted are rejected. We distinguish between two types of errors. Type I error is the one committed by rejecting a correct hypothesis. Type II is that of accepting a wrong hypothesis. It is desired that both types of errors will occur simultaneously with small probabilities. Both precision in estimation or small error probabilities in testing depend on the statistics used (estimators or test functions) and on the sample size. In this paper, we present sampling procedures that attain the desired objectives. In Sec. 2, we discuss estimation of the parameters of a binomial distribution. In Sec. 3, more general results about estimation of expected values are presented. In Sec. 4, we discuss the Wald Sequential Probability Ratio Test (SPRT), which has optimal properties for testing two simple hypotheses.

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Wagner, Peter J. "Phylogenetic analyses and the fossil record: Tests and inferences, hypotheses and models." Paleobiology 26, S4 (2000): 341–71. http://dx.doi.org/10.1017/s0094837300027007.

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Tree-based paleobiological studies use inferred phylogenies as models to test hypotheses about macroevolution and the quality of the fossil record. Such studies raise two concerns. The first is how model trees might bias results. The second is testing hypotheses about parameters that affect tree inference.Bias introduced by model trees is explored for tree-based assessments of the quality of the fossil record. Several nuisance parameters affect tree-based metrics, including consistency of sampling probability, rates of speciation / extinction, patterns of speciation, applied taxonomic philosophy, and assumed taxonomy. The first two factors affect probabilistic assessments of sampling, but also can be tested and accommodated in sophisticated probability tests. However, the final three parameters (and the assumption of a correct phylogeny) do not affect probabilistic assessments.Often paleobiologists wish to test hypotheses such as rates of character change or rates of preservation. Assumptions about such parameters are necessary in simple phylogenetic methods, even if the assumptions are that rates are homogeneous or that sampling is irrelevant. Likelihood tests that evaluate phylogenies in light of stratigraphic data and / or alternative hypotheses of character evolution can reduce assumptions about unknowns by testing numerous unknowns simultaneously. Such tests have received numerous criticisms, largely based in philosophy. However, such criticisms are based on incorrect depictions of the logical structures of parsimony and likelihood, misunderstandings about when arguments are probabilistic (as opposed to Boolean), overly restrictive concepts of when data can test a hypothesis, and simply incorrect definitions of some terms.Likelihood methods can test multiparameter hypotheses about phylogeny and character evolution (i.e., rates, independence, etc.). The best hypothesis positing a single rate of independent character change (with no variation among character states) is determined for each topology. Hypotheses about rate variation among characters or across phylogeny, character independence, and different patterns of state evolution then are examined until one finds the simplest (i.e., fewest varying parameters) hypothesis that cannot be rejected given knowledge of a more complicated hypothesis. This is repeated for alternative topologies. An example is presented using hyaenids. Two trees are contrasted, one of which requires the minimum necessary steps and the other of which requires at least seven additional steps. Given either tree, likelihood rejects fewer than three general rates of character change and also rejects the hypothesis of independence among the characters. However, hypotheses of changes in rates across the tree do not add substantially to the tree likelihood. The likelihoods of the trees given stratigraphic data also are determined. Both morphologic and stratigraphic data suggest that the multiparameter hypothesis including the parsimony tree is significantly less likely than the multiparameter hypothesis including a different tree.

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Zheng, Lu, and Marvin Zelen. "Urn sampling, interval censoring and proportional hazard models." Statistical Modelling 9, no. 4 (December 2009): 361–79. http://dx.doi.org/10.1177/1471082x0900900406.

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This paper proposes a new distribution-free statistical method for testing hypotheses about covariates for survival data having simultaneously right-, left- and interval-censored survival times. The new test is motivated by the analogue between urn sampling and the Cox’s proportional hazard models. Investigations of the significance levels and power as a function of the proportion of interval-censored observations and interval length show that the test performs well for most censoring situations encountered in practice. Simulation results also suggest that there is negligible loss of power in the practical situation in which the mean interval length for interval-censored observations is less than the mean survival time. This holds even with heavy interval censoring. Comparison with the widely used Mantel’s method for comparing two groups shows that the power of the new method appears to be superior. Furthermore, the test is relatively simple to carry out and generalizes to comparing k populations as well as the testing of general linear hypothesis for arbitrary covariates.

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Harjunar, Hariani, and Inayanti Fatwa. "The Effect of Mathematical Anxiety on the Understanding of Mathematical Concepts in Class XI Students of SMAN 5 Sinjai." EduLine: Journal of Education and Learning Innovation 2, no. 4 (December 18, 2022): 498–501. http://dx.doi.org/10.35877/454ri.eduline1377.

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This research aims to determine the influence of mathematical anxiety on the understanding of mathematical concepts. The method used an investigation and sampling method with a simple random sampling technique, the sample of which was 90 students. Analysis in the context of testing research hypotheses using linear regression analysis tests, with the results of hypothesis tests producing the influence of mathematical anxiety on the understanding of mathematical concepts.

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Nurdiono, Nurdiono, Farichah Farichah, Lego Waspodo, Doni Sagitarian Warganegara, Edwin Mirfazli, and Amrizah Kamaluddin. "ANTECEDENTS AND CONSEQUENCES OF PSYCHOLOGICAL EMPOWERMENT AND ROLE CLARITY AS AN INTERVENING VARIABLE." Humanities & Social Sciences Reviews 7, no. 6 (December 16, 2019): 680–90. http://dx.doi.org/10.18510/hssr.2019.76102.

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Purpose: This study aims to examine the effect of decentralization in decision making, psychological empowerment, and clarity of role in the implementation of the Regional Financial Information System (SIKD). Methodology: The sampling technique in this study is by using the Convenience Sampling technique. Results: The results of hypothesis testing show that there are six supported hypotheses and two rejected hypotheses. Implications: The implementation of the Regional Financial Information System (SIKD) and the consequences of implementing SIKD on performance by mediating dysfunctional behavior in the Regional Work Unit (SKPD) implementers in Lampung Province.

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Betancur‐R., Ricardo, Dahiana Arcila, Richard P. Vari, Lily C. Hughes, Claudio Oliveira, Mark H. Sabaj, and Guillermo Ortí. "Phylogenomic incongruence, hypothesis testing, and taxonomic sampling: The monophyly of characiform fishes*." Evolution 73, no. 2 (December 4, 2018): 329–45. http://dx.doi.org/10.1111/evo.13649.

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Novotny, Vojtech, and Pavel Drozd. "Sampling error can cause false rejection of the core-satellite species hypothesis." Oecologia 126, no. 3 (February 2001): 360–62. http://dx.doi.org/10.1007/s004420000528.

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Asghari, Samaneh, and Bahram Sadeghpour Gildeh. "Hypothesis testing for the lifetime performance index based on ranked set sampling." Total Quality Management & Business Excellence 31, no. 9-10 (May 31, 2018): 1022–40. http://dx.doi.org/10.1080/14783363.2018.1459543.

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He, Shaoming, Hyo-Sang Shin, and Antonios Tsourdos. "Track-Oriented Multiple Hypothesis Tracking Based on Tabu Search and Gibbs Sampling." IEEE Sensors Journal 18, no. 1 (January 1, 2018): 328–39. http://dx.doi.org/10.1109/jsen.2017.2758846.

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Samy, Chander N., and Joy Hirsch. "Comparison of human and monkey retinal photoreceptor sampling mosaics." Visual Neuroscience 3, no. 3 (September 1989): 281–85. http://dx.doi.org/10.1017/s0952523800010038.

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AbstractWe test the hypothesis that the diameters of foveal and near-foveal rods and cones for one well-studied human photoreceptor mosaic and one well-studied monkey photoreceptor mosaic (Macaca fascicularis) a scaled relative to focal length. We conclude that this hypothesis is not supported. Rather than being scali proportionally, the sizes of the rods and cones, respectively, are nearly equivalent for both the human ar monkey resulting in an effectively finer retinal grain for the larger human eye. Furthermore, the human density exceeds the monkey rod density beyond about 1 deg of retinal eccentricity. These results suggest variation across primate species is reflected in retinal sampling strategies.

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Bez, Nicolas. "Global fish abundance estimation from regular sampling: the geostatistical transitive method." Canadian Journal of Fisheries and Aquatic Sciences 59, no. 12 (December 1, 2002): 1921–31. http://dx.doi.org/10.1139/f02-155.

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This article deals with the estimation of fish biomass based on regular samplings. The geostatistical transitive method is a design-based spatially explicit method based on few and falsifiable assumptions concerning the sampling strategy. The falsifiability of a hypothesis corresponds to our capacity to control its adequacy to field data in practice. We first describe the basics of the method, mention the questions relative to the covariogram estimation, the units, and the projections of the coordinates, and explain how to fit the model to the experimental covariogram. We then apply the method to an ICES (International Council for the Exploration of the Sea) triennial mackerel egg survey, with regular sampling, and to a Moroccan octopus survey, with regular stratified sampling. To compare the present technique with existing methods, the number and the falsifiability of their respective hypotheses are considered in addition to the bias, the convergence, and the estimation variance. As is often the case, data are assumed to be synoptic, and we discuss two examples of spatiotemporal methods.

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Yudaruddin, Rizky. "MARKET STRUCTURE, CONDUCT AND PERFORMANCE: EVIDENCE FROM INDONESIA BANKING INDUSTRY." EKUITAS (Jurnal Ekonomi dan Keuangan) 19, no. 3 (September 6, 2018): 299–317. http://dx.doi.org/10.24034/j25485024.y2015.v19.i3.126.

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Indonesian Banking Architecture Policies (API) since 2004 has resulted in the rising of banks concentration. This increase of banks concentration raises two opposing hypotheses,structure-conduct- performance (SCP) and efficient-performance hypothesis. SCP approach is a structural approach. This approach considers that the level of profits which the bank acquired is affected by the market structure and the degree of competition.The decreasing level of competition and the increasing in concentration in an industry will lead to increased profits for these industries.This study aims to prove, whether banks in Indonesia in 2009-2013 supportstructure-conduct-performanceor efficient-performance hypotheses. The sampling method used was purposive sampling. Using banks’ financial statement data sourced fromBank Indonesia, which then analyzed with panel data regression in e-views 8 program. It’s found that banks in Indonesia support the efficient hypothesis. However, the banks efficiency has yet encourage low interest practice and thus reducing the competitiveness of the Indonesian economy in the face ofASEAN Community 2015.

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Shimkin, Nahum. "Extremal large deviations in controlled i.i.d. processes with applications to hypothesis testing." Advances in Applied Probability 25, no. 4 (December 1993): 875–94. http://dx.doi.org/10.2307/1427796.

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We consider a controlled i.i.d. process, where several i.i.d. sources are sampled sequentially. At each time instant, a controller determines from which source to obtain the next sample. Any causal sampling policy, possibly history-dependent, may be employed. The purpose is to characterize the extremal large deviations of the sample mean, namely to obtain asymptotic rate bounds (similar to and extending Cramér's theorem) which hold uniformly over all sampling policies. Lower and upper bounds are obtained, and it is shown that in many (but not all) cases stationary sampling policies are sufficient to obtain the extremal large deviations rates. These results are applied to a hypothesis testing problem, where data samples may be sequentially chosen from several i.i.d. sources (representing different types of experiments). The analysis provides asymptotic estimates for the error probabilities, corresponding both to optimal and to worst-case sampling policies.

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Shimkin, Nahum. "Extremal large deviations in controlled i.i.d. processes with applications to hypothesis testing." Advances in Applied Probability 25, no. 04 (December 1993): 875–94. http://dx.doi.org/10.1017/s0001867800025799.

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We consider a controlled i.i.d. process, where several i.i.d. sources are sampled sequentially. At each time instant, a controller determines from which source to obtain the next sample. Any causal sampling policy, possibly history-dependent, may be employed. The purpose is to characterize the extremal large deviations of the sample mean, namely to obtain asymptotic rate bounds (similar to and extending Cramér's theorem) which hold uniformly over all sampling policies. Lower and upper bounds are obtained, and it is shown that in many (but not all) cases stationary sampling policies are sufficient to obtain the extremal large deviations rates. These results are applied to a hypothesis testing problem, where data samples may be sequentially chosen from several i.i.d. sources (representing different types of experiments). The analysis provides asymptotic estimates for the error probabilities, corresponding both to optimal and to worst-case sampling policies.

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Farah, FARAH NUR AZIZAH, and Firdayetti. "Effect of Financial Performance and Business Risk on Capital Structure." Journal of Applied Management and Business (JAMB) 3, no. 2 (December 21, 2022): 55–64. http://dx.doi.org/10.37802/jamb.v3i2.269.

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The purpose of the following research is to analyze and obtain the results of profitability, cash flow and business losses on company profits and changes in financial structure. The following research is a quantitative analysis research using descriptive method. The following research population is all transportation and logistics companies listed on the Indonesia Stock Exchange for the three period. The sampling method used is purposive sampling and the research method used in the following research is multiple linear analysis, classical hypothesis testing and hypothesis testing using the Statistical Package for Social Sciences (SPSS) version twenty two program to test hypotheses. The following research results show that the effect of debt and business risk/loss has a significant effect on financial planning or is called capital structure, while profit is not so significant.

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SUN, HONGWEI, and QIANG WU. "INDEFINITE KERNEL NETWORK WITH DEPENDENT SAMPLING." Analysis and Applications 11, no. 05 (September 2013): 1350020. http://dx.doi.org/10.1142/s0219530513500206.

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We study the asymptotical properties of indefinite kernel network with coefficient regularization and dependent sampling. The framework under investigation is different from classical kernel learning. Positive definiteness is not required by the kernel function and the samples are allowed to be weakly dependent with the dependence measured by a strong mixing condition. By a new kernel decomposition technique introduced in [27], two reproducing kernel Hilbert spaces and their associated kernel integral operators are used to characterize the properties and learnability of the hypothesis function class. Capacity independent error bounds and learning rates are deduced.

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Slatkin, Montgomery, and Bruce Rannala. "The Sampling Distribution of Disease-Associated Alleles." Genetics 147, no. 4 (December 1, 1997): 1855–61. http://dx.doi.org/10.1093/genetics/147.4.1855.

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Abstract A theory is developed that provides the sampling distribution of low frequency alleles at a single locus under the assumption that each allele is the result of a unique mutation. The numbers of copies of each allele is assumed to follow a linear birth-death process with sampling. If the population is of constant size, standard results from theory of birth-death processes show that the distribution of numbers of copies of each allele is logarithmic and that the joint distribution of numbers of copies of k alleles found in a sample of size n follows the Ewens sampling distribution. If the population from which the sample was obtained was increasing in size, if there are different selective classes of alleles, or if there are differences in penetrance among alleles, the Ewens distribution no longer applies. Likelihood functions for a given set of observations are obtained under different alternative hypotheses. These results are applied to published data from the BRCA1 locus (associated with early onset breast cancer) and the factor VIII locus (associated with hemophilia A) in humans. In both cases, the sampling distribution of alleles allows rejection of the null hypothesis, but relatively small deviations from the null model can account for the data. In particular, roughly the same population growth rate appears consistent with both data sets.

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Wilks, D. S. "Indices of Rank Histogram Flatness and Their Sampling Properties." Monthly Weather Review 147, no. 2 (February 1, 2019): 763–69. http://dx.doi.org/10.1175/mwr-d-18-0369.1.

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Abstract Quantitative evaluation of the flatness of the verification rank histogram can be approached through formal hypothesis testing. Traditionally, the familiar χ2 test has been used for this purpose. Recently, two alternatives—the reliability index (RI) and an entropy statistic (Ω)—have been suggested in the literature. This paper presents approximations to the sampling distributions of these latter two rank histogram flatness metrics, and compares the statistical power of tests based on the three statistics, in a controlled setting. The χ2 test is generally most powerful (i.e., most sensitive to violations of the null hypothesis of rank uniformity), although for overdispersed ensembles and small sample sizes, the test based on the entropy statistic Ω is more powerful. The RI-based test is preferred only for unbiased forecasts with small ensembles and very small sample sizes.

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Butler, Richard J., Roger B. J. Benson, Matthew T. Carrano, Philip D. Mannion, and Paul Upchurch. "Sea level, dinosaur diversity and sampling biases: investigating the ‘common cause’ hypothesis in the terrestrial realm." Proceedings of the Royal Society B: Biological Sciences 278, no. 1709 (September 29, 2010): 1165–70. http://dx.doi.org/10.1098/rspb.2010.1754.

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The fossil record is our primary window onto the diversification of ancient life, but there are widespread concerns that sampling biases may distort observed palaeodiversity counts. Such concerns have been reinforced by numerous studies that found correlations between measures of sampling intensity and observed diversity. However, correlation does not necessarily mean that sampling controls observed diversity: an alternative view is that both sampling and diversity may be driven by some common factor (e.g. variation in continental flooding driven by sea level). The latter is known as the ‘common cause’ hypothesis. Here, we present quantitative analyses of the relationships between dinosaur diversity, sampling of the dinosaur fossil record, and changes in continental flooding and sea level, providing new insights into terrestrial common cause. Although raw data show significant correlations between continental flooding/sea level and both observed diversity and sampling, these correlations do not survive detrending or removal of short-term autocorrelation. By contrast, the strong correlation between diversity and sampling is robust to various data transformations. Correlations between continental flooding/sea level and taxic diversity/sampling result from a shared upward trend in all data series, and short-term changes in continental flooding/sea level and diversity/sampling do not correlate. The hypothesis that global dinosaur diversity is tied to sea-level fluctuations is poorly supported, and terrestrial common cause is unsubstantiated as currently conceived. Instead, we consider variation in sampling to be the preferred null hypothesis for short-term diversity variation in the Mesozoic terrestrial realm.

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Levi, Karin, Adi Shoham, Iftach Amir, and Amit Bernstein. "The Daily Dose-Response Hypothesis of Mindfulness Meditation Practice: An Experience Sampling Study." Psychosomatic Medicine 83, no. 6 (January 20, 2021): 624–30. http://dx.doi.org/10.1097/psy.0000000000000912.

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Haila, Yrjo, Ilpo K. Hanski, and Suvi Raivio. "Turnover of Breeding Birds in Small Forest Fragments: The "Sampling" Colonization Hypothesis Corroborated." Ecology 74, no. 3 (April 1993): 714–25. http://dx.doi.org/10.2307/1940799.

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Swendsen, Joel D., Howard Tennen, Margaret Anne Carney, Glenn Affleck, Amy Willard, and Amber Hromi. "Mood and alcohol consumption: An experience sampling test of the self-medication hypothesis." Journal of Abnormal Psychology 109, no. 2 (2000): 198–204. http://dx.doi.org/10.1037/0021-843x.109.2.198.

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Sawyer, John E. "Hypothesis sampling, construction, or adjustment: How are inferences about nonlinear monotonic contingencies developed?" Organizational Behavior and Human Decision Processes 49, no. 1 (June 1991): 124–50. http://dx.doi.org/10.1016/0749-5978(91)90045-u.

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Marsola, Júlio C. A., Gabriel S. Ferreira, Max C. Langer, David J. Button, and Richard J. Butler. "Increases in sampling support the southern Gondwanan hypothesis for the origin of dinosaurs." Palaeontology 62, no. 3 (December 12, 2018): 473–82. http://dx.doi.org/10.1111/pala.12411.

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