Relevant bibliographies by topics / Testing hypothesis

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Testing hypothesis'

Author: Grafiati
Published: 4 June 2021
Last updated: 18 February 2022

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Testing hypothesis.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Testing hypothesis"

1

Bashir, Josefeena. "Hypothesis Testing." Scientific Journal of India 3, no. 1 (December 31, 2018): 62–63. http://dx.doi.org/10.21276/24565644/2018.v3.i1.21.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Daya, Salim. "Hypothesis testing." Evidence-based Obstetrics & Gynecology 1, no. 2 (June 1999): 47. http://dx.doi.org/10.1054/ebog.1999.0052.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Sheikh, Aziz, and Adrian Cook. "Hypothesis testing." Primary Care Respiratory Journal 9, no. 1 (June 2000): 16–17. http://dx.doi.org/10.1038/pcrj.2000.11.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Davis, Roger B., and Kenneth J. Mukamal. "Hypothesis Testing." Circulation 114, no. 10 (September 5, 2006): 1078–82. http://dx.doi.org/10.1161/circulationaha.105.586461.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Gauvreau, Kimberlee. "Hypothesis Testing." Circulation 114, no. 14 (October 3, 2006): 1545–48. http://dx.doi.org/10.1161/circulationaha.105.586487.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Yarandi, Hossein N. "Hypothesis Testing." Clinical Nurse Specialist 10, no. 4 (July 1996): 186–88. http://dx.doi.org/10.1097/00002800-199607000-00009.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Allua, Shane, and Cheryl Bagley Thompson. "Hypothesis Testing." Air Medical Journal 28, no. 3 (May 2009): 108–53. http://dx.doi.org/10.1016/j.amj.2009.03.002.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Pereira, Sandra M. C., and Gavin Leslie. "Hypothesis testing." Australian Critical Care 22, no. 4 (November 2009): 187–91. http://dx.doi.org/10.1016/j.aucc.2009.08.003.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Sanbonmatsu, David M., Steven S. Posavac, Frank R. Kardes, and Susan P. Mantel. "Selective hypothesis testing." Psychonomic Bulletin & Review 5, no. 2 (June 1998): 197–220. http://dx.doi.org/10.3758/bf03212944.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Marino, Ralph J. "Statistical hypothesis testing." Archives of Physical Medicine and Rehabilitation 76, no. 6 (June 1995): 587–88. http://dx.doi.org/10.1016/s0003-9993(95)80518-4.

Full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Testing hypothesis"

1

Zhang, Zhongfa. "Multiple hypothesis testing for finite and infinite number of hypotheses." online version, 2005. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=case1121461130.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Chwialkowski, K. P. "Topics in kernal hypothesis testing." Thesis, University College London (University of London), 2016. http://discovery.ucl.ac.uk/1519607/.

Full text
Abstract:
This thesis investigates some unaddressed problems in kernel nonparametric hypothesis testing. The contributions are grouped around three main themes: Wild Bootstrap for Degenerate Kernel Tests. A wild bootstrap method for nonparametric hypothesis tests based on kernel distribution embeddings is proposed. This bootstrap method is used to construct provably consistent tests that apply to random processes. It applies to a large group of kernel tests based on V-statistics, which are degenerate under the null hypothesis, and non-degenerate elsewhere. In experiments, the wild bootstrap gives strong performance on synthetic examples, on audio data, and in performance benchmarking for the Gibbs sampler. A Kernel Test of Goodness of Fit. A nonparametric statistical test for goodness-of-fit is proposed: given a set of samples, the test determines how likely it is that these were generated from a target density function. The measure of goodness-of-fit is a divergence constructed via Stein's method using functions from a Reproducing Kernel Hilbert Space. Construction of the test is based on the wild bootstrap method. We apply our test to quantifying convergence of approximate Markov Chain Monte Carlo methods, statistical model criticism, and evaluating quality of fit vs model complexity in nonparametric density estimation. Fast Analytic Functions Based Two Sample Test. A class of nonparametric two-sample tests with a cost linear in the sample size is proposed. Two tests are given, both based on an ensemble of distances between analytic functions representing each of the distributions. Experiments on artificial benchmarks and on challenging real-world testing problems demonstrate good power/time tradeoff retained even in high dimensional problems. The main contributions to science are the following. We prove that the kernel tests based on the wild bootstrap method tightly control the type one error on the desired level and are consistent i.e. type two error drops to zero with increasing number of samples. We construct a kernel goodness of fit test that requires only knowledge of the density up to an normalizing constant. We use this test to construct first consistent test for convergence of Markov Chains and use it to quantify properties of approximate MCMC algorithms. Finally, we construct a linear time two-sample test that uses new, finite dimensional feature representation of probability measures.
APA, Harvard, Vancouver, ISO, and other styles
3

Varshney, Kush R. (Kush Raj). "Frugal hypothesis testing and classification." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/60182.

Full text
Abstract:
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 157-175).
The design and analysis of decision rules using detection theory and statistical learning theory is important because decision making under uncertainty is pervasive. Three perspectives on limiting the complexity of decision rules are considered in this thesis: geometric regularization, dimensionality reduction, and quantization or clustering. Controlling complexity often reduces resource usage in decision making and improves generalization when learning decision rules from noisy samples. A new margin-based classifier with decision boundary surface area regularization and optimization via variational level set methods is developed. This novel classifier is termed the geometric level set (GLS) classifier. A method for joint dimensionality reduction and margin-based classification with optimization on the Stiefel manifold is developed. This dimensionality reduction approach is extended for information fusion in sensor networks. A new distortion is proposed for the quantization or clustering of prior probabilities appearing in the thresholds of likelihood ratio tests. This distortion is given the name mean Bayes risk error (MBRE). The quantization framework is extended to model human decision making and discrimination in segregated populations.
by Kush R. Varshney.
Ph.D.
APA, Harvard, Vancouver, ISO, and other styles
4

Vilela, Lucas Pimentel. "Hypothesis testing in econometric models." reponame:Repositório Institucional do FGV, 2015. http://hdl.handle.net/10438/18249.

Full text
Abstract:
Submitted by Lucas Pimentel Vilela (lucaspimentelvilela@gmail.com) on 2017-05-04T01:19:37Z No. of bitstreams: 1 Hypothesis Testing in Econometric Models - Vilela 2017.pdf: 2079231 bytes, checksum: d0387462f36ab4ab7e5d33163bb68416 (MD5)
Approved for entry into archive by Maria Almeida (maria.socorro@fgv.br) on 2017-05-15T19:31:43Z (GMT) No. of bitstreams: 1 Hypothesis Testing in Econometric Models - Vilela 2017.pdf: 2079231 bytes, checksum: d0387462f36ab4ab7e5d33163bb68416 (MD5)
Made available in DSpace on 2017-05-15T19:32:18Z (GMT). No. of bitstreams: 1 Hypothesis Testing in Econometric Models - Vilela 2017.pdf: 2079231 bytes, checksum: d0387462f36ab4ab7e5d33163bb68416 (MD5) Previous issue date: 2015-12-11
This thesis contains three chapters. The first chapter considers tests of the parameter of an endogenous variable in an instrumental variables regression model. The focus is on one-sided conditional t-tests. Theoretical and numerical work shows that the conditional 2SLS and Fuller t-tests perform well even when instruments are weakly correlated with the endogenous variable. When the population F-statistic is as small as two, the power is reasonably close to the power envelopes for similar and non-similar tests which are invariant to rotation transformations of the instruments. This finding is surprising considering the poor performance of two-sided conditional t-tests found in Andrews, Moreira, and Stock (2007). These tests have bad power because the conditional null distributions of t-statistics are asymmetric when instruments are weak. Taking this asymmetry into account, we propose two-sided tests based on t-statistics. These novel tests are approximately unbiased and can perform as well as the conditional likelihood ratio (CLR) test. The second and third chapters are interested in maxmin and minimax regret tests for broader hypothesis testing problems. In the second chapter, we present maxmin and minimax regret tests satisfying more general restrictions than the alpha-level and the power control over all alternative hypothesis constraints. More general restrictions enable us to eliminate trivial known tests and obtain tests with desirable properties, such as unbiasedness, local unbiasedness and similarity. In sequence, we prove that both tests always exist and under suficient assumptions, they are Bayes tests with priors that are solutions of an optimization problem, the dual problem. In the last part of the second chapter, we consider testing problems that are invariant to some group of transformations. Under the invariance of the hypothesis testing, the Hunt-Stein Theorem proves that the search for maxmin and minimax regret tests can be restricted to invariant tests. We prove that the Hunt-Stein Theorem still holds under the general constraints proposed. In the last chapter we develop a numerical method to implement maxmin and minimax regret tests proposed in the second chapter. The parametric space is discretized in order to obtain testing problems with a finite number of restrictions. We prove that, as the discretization turns finer, the maxmin and the minimax regret tests satisfying the finite number of restrictions have the same alternative power of the maxmin and minimax regret tests satisfying the general constraints. Hence, we can numerically implement tests for a finite number of restrictions as an approximation for the tests satisfying the general constraints. The results in the second and third chapters extend and complement the maxmin and minimax regret literature interested in characterizing and implementing both tests.
Esta tese contém três capítulos. O primeiro capítulo considera testes de hipóteses para o coeficiente de regressão da variável endógena em um modelo de variáveis instrumentais. O foco é em testes-t condicionais para hipóteses unilaterais. Trabalhos teóricos e numéricos mostram que os testes-t condicionais centrados nos estimadores de 2SLS e Fuller performam bem mesmo quando os instrumentos são fracamente correlacionados com a variável endógena. Quando a estatística F populacional é menor que dois, o poder é razoavelmente próximo do poder envoltório para testes que são invariantes a transformações que rotacionam os instrumentos (similares ou não similares). Este resultado é surpreendente considerando a baixa performance dos testes-t condicionais para hipóteses bilaterais apresentado em Andrews, Moreira, and Stock (2007). Estes testes possuem baixo poder porque as distribuições das estatísticas-t na hipótese nula são assimétricas quando os instrumentos são fracos. Explorando tal assimetria, nós propomos testes para hipóteses bilaterais baseados em estatísticas-t. Estes testes são aproximadamente não viesados e podem performar tão bem quanto o teste de razão de máxima verossimilhança condicional. No segundo e no terceiro capítulos, nosso interesse é em testes do tipo maxmin e minimax regret para testes de hipóteses mais gerais. No segundo capítulo, nós apresentamos testes maxmin e minimax regret que satisfazem restrições mais gerais que as restrições de tamanho e de controle sobre todo o poder na hipótese alternativa. Restrições mais gerais nos possibilitam eliminar testes triviais e obter testes com propriedades desejáveis, como por exemplo não viés, não viés local e similaridade. Na sequência, nós provamos que ambos os testes existem e, sob condições suficientes, eles são testes Bayesianos com priors que são solução de um problema de otimização, o problema dual. Na última parte do segundo capítulo, nós consideramos testes de hipóteses que são invariantes à algum grupo de transformações. Sob invariância, o Teorema de Hunt-Stein implica que a busca por testes maxmin e minimax regret pode ser restrita a testes invariantes. Nós provamos que o Teorema de Hunt-Stein continua válido sob as restrições gerais propostas. No último capítulo, nós desenvolvemos um procedimento numérico para implementar os testes maxmin e minimax regret propostos no segundo capítulo. O espaço paramétrico é discretizado com o objetivo de obter testes de hipóteses com um número finito de pontos. Nós provamos que, ao considerarmos partições mais finas, os testes maxmin e minimax regret que satisfazem um número finito de pontos possuem o mesmo poder na hipótese alternativa que os testes maxmin e minimax regret que satisfazem as restrições gerais. Portanto, nós podemos implementar numericamente os testes que satisfazem um número finito de pontos como aproximação aos testes que satisfazem as restrições gerais.
APA, Harvard, Vancouver, ISO, and other styles
5

Lapenta, Elia. "Three Essays in Hypothesis Testing." Thesis, Toulouse 1, 2020. http://www.theses.fr/2020TOU10053.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Donmez, Ayca. "Adaptive Estimation And Hypothesis Testing Methods." Phd thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/3/12611724/index.pdf.

Full text
Abstract:
For statistical estimation of population parameters, Fisher&rsquo
s maximum likelihood estimators (MLEs) are commonly used. They are consistent, unbiased and efficient, at any rate for large n. In most situations, however, MLEs are elusive because of computational difficulties. To alleviate these difficulties, Tiku&rsquo
s modified maximum likelihood estimators (MMLEs) are used. They are explicit functions of sample observations and easy to compute. They are asymptotically equivalent to MLEs and, for small n, are equally efficient. Moreover, MLEs and MMLEs are numerically very close to one another. For calculating MLEs and MMLEs, the functional form of the underlying distribution has to be known. For machine data processing, however, such is not the case. Instead, what is reasonable to assume for machine data processing is that the underlying distribution is a member of a broad class of distributions. Huber assumed that the underlying distribution is long-tailed symmetric and developed the so called M-estimators. It is very desirable for an estimator to be robust and have bounded influence function. M-estimators, however, implicitly censor certain sample observations which most practitioners do not appreciate. Tiku and Surucu suggested a modification to Tiku&rsquo
s MMLEs. The new MMLEs are robust and have bounded influence functions. In fact, these new estimators are overall more efficient than M-estimators for long-tailed symmetric distributions. In this thesis, we have proposed a new modification to MMLEs. The resulting estimators are robust and have bounded influence functions. We have also shown that they can be used not only for long-tailed symmetric distributions but for skew distributions as well. We have used the proposed modification in the context of experimental design and linear regression. We have shown that the resulting estimators and the hypothesis testing procedures based on them are indeed superior to earlier such estimators and tests.
APA, Harvard, Vancouver, ISO, and other styles
7

Allison, James Samuel. "Bootstrap-based hypothesis testing / J.S. Allison." Thesis, North-West University, 2008. http://hdl.handle.net/10394/3701.

Full text
Abstract:
One of the main objectives of this dissertation is the development of a new method of evaluating the performance of bootstrap-based tests. The evaluation method that is currently in use in the literature has some major shortcomings, for example, it does not allow one to determine the robustness of a bootstrap estimator of a critical value. This is because the evaluation and the estimation are based on the same data. This traditional method of evaluation often leads to too optimistic probability of type I errors when bootstrap critical values are used. We show how this new, more robust, method can detect defects of bootstrap estimated critical values which cannot be observed if one uses the current evaluation method. Based on the new evaluation method, some theoretical properties regarding the bootstrap critical value are derived when testing for the mean in a univariate population. These theoretical findings again highlight the importance of the two guidelines proposed by Hall and Wilson (1991) for bootstrap-based testing, namely that resampling must be done in a way that reflects the null hypothesis and bootstrap tests should be based on test statistics that are pivotal (or asymptotically pivotal). We also developed a new nonparametric bootstrap test for Spearman's rho and, based on the results obtained from a Monte-Carlo study, we recommend that this new test should be used when testing for Spearman's rho. A semiparametric test based on copulas was also developed as a useful benchmark tool for measuring the performance of the nonparametric test. Other research objectives of this dissertation include, among others, a brief overview of the nonparametric bootstrap and a general formulation of methods which can be used to apply the bootstrap correctly when conducting hypothesis testing.
Thesis (Ph.D. (Statistics))--North-West University, Potchefstroom Campus, 2009.
APA, Harvard, Vancouver, ISO, and other styles
8

Lewsey, James Daniel. "Hypothesis testing in unbalanced experimental designs." Thesis, Glasgow Caledonian University, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.322213.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Vu, Hung Thi Hong. "Testing the individual effective dose hypothesis." Connect to this title online, 2009. http://etd.lib.clemson.edu/documents/1247508549/.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Sestok, Charles K. (Charles Kasimer). "Data selection in binary hypothesis testing." Thesis, Massachusetts Institute of Technology, 2003. http://hdl.handle.net/1721.1/16613.

Full text
Abstract:
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, February 2004.
Includes bibliographical references (p. 119-123).
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Traditionally, statistical signal processing algorithms are developed from probabilistic models for data. The design of the algorithms and their ultimate performance depend upon these assumed models. In certain situations, collecting or processing all available measurements may be inefficient or prohibitively costly. A potential technique to cope with such situations is data selection, where a subset of the measurements that can be collected and processed in a cost-effective manner is used as input to the signal processing algorithm. Careful evaluation of the selection procedure is important, since the probabilistic description of distinct data subsets can vary significantly. An algorithm designed for the probabilistic description of a poorly chosen data subset can lose much of the potential performance available to a well-chosen subset. This thesis considers algorithms for data selection combined with binary hypothesis testing. We develop models for data selection in several cases, considering both random and deterministic approaches. Our considerations are divided into two classes depending upon the amount of information available about the competing hypotheses. In the first class, the target signal is precisely known, and data selection is done deterministically. In the second class, the target signal belongs to a large class of random signals, selection is performed randomly, and semi-parametric detectors are developed.
by Charles K. Sestok, IV.
Ph.D.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Books on the topic "Testing hypothesis"

1

Bonnini, Stefano, Livio Corain, Marco Marozzi, and Luigi Salmaso. Nonparametric Hypothesis Testing. Chichester, UK: John Wiley & Sons, Ltd, 2014. http://dx.doi.org/10.1002/9781118763490.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Hypothesis testing behavior. Philadelphia: Psychology Press, 2001.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
3

Testing statistical hypotheses. 2nd ed. New York: Wiley, 1986.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
4

Testing statistical hypotheses. 2nd ed. New York: Springer, 1997.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
5

1960-, Romano Joseph P., ed. Testing statistical hypotheses. 3rd ed. New York: Springer, 2005.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
6

Lehmann, E. L. Testing statistical hypotheses. 2nd ed. New York: Springer, 1986.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
7

Testing statistical hypotheses. 2nd ed. Pacific Grove, Calif: Wadsworth & Brooks/Cole Advanced Books & Software, 1991.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
8

Lehmann, E. L. Testing statistical hypotheses. 2nd ed. New York: Springer, 1997.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
9

Tiku, Moti Lal. Robust estimation and hypothesis testing. New Delhi: New Age International (P) Ltd., Publishers, 2004.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
10

Gül, Gökhan. Robust and Distributed Hypothesis Testing. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-49286-5.

Full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Book chapters on the topic "Testing hypothesis"

1

Johansson, Lars-Göran. "Hypotheses and Hypothesis Testing." In Philosophy of Science for Scientists, 41–61. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-26551-3_3.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Bowers, David. "Hypothesis Testing." In Statistics for Economics and Business, 137–63. London: Palgrave Macmillan UK, 1991. http://dx.doi.org/10.1007/978-1-349-21346-7_12.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Rees, D. G. "Hypothesis testing." In Essential Statistics, 100–115. Boston, MA: Springer US, 1989. http://dx.doi.org/10.1007/978-1-4899-7260-6_10.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Koch, Karl-Rudolf. "Hypothesis testing." In Bayesian Inference with Geodetic Applications, 40–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/bfb0048706.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Klein, John P., and Melvin L. Moeschberger. "Hypothesis Testing." In Statistics for Biology and Health, 201–42. New York, NY: Springer New York, 2003. http://dx.doi.org/10.1007/0-387-21645-6_7.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Härdle, Wolfgang Karl, and Léopold Simar. "Hypothesis Testing." In Applied Multivariate Statistical Analysis, 195–229. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-26006-4_7.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Booth, Tom, Alex Doumas, and Aja Louise Murray. "Hypothesis Testing." In Encyclopedia of Personality and Individual Differences, 2116–19. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-319-24612-3_1310.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Miller, A. J. "Hypothesis testing." In Subset Selection in Regression, 84–109. Boston, MA: Springer US, 1990. http://dx.doi.org/10.1007/978-1-4899-2939-6_4.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Härdle, Wolfgang Karl, and Zdeněk Hlávka. "Hypothesis Testing." In Multivariate Statistics, 103–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-642-36005-3_7.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Ubøe, Jan. "Hypothesis Testing." In Springer Texts in Business and Economics, 177–200. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70936-9_9.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Testing hypothesis"

1

Katz, Gil, Pablo Piantanida, and Merouane Debbah. "Collaborative distributed hypothesis testing with general hypotheses." In 2016 IEEE International Symposium on Information Theory (ISIT). IEEE, 2016. http://dx.doi.org/10.1109/isit.2016.7541590.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Zykov, Roman. "Hypothesis Testing." In RecSys '16: Tenth ACM Conference on Recommender Systems. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2959100.2959127.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Li, Yun, Sirin Nitinawarat, and Venugopal V. Veeravalli. "Universal outlier hypothesis testing." In 2013 IEEE International Symposium on Information Theory (ISIT). IEEE, 2013. http://dx.doi.org/10.1109/isit.2013.6620710.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Jin, Yulu, and Lifeng Lai. "Adversarially Robust Hypothesis Testing." In 2019 53rd Asilomar Conference on Signals, Systems, and Computers. IEEE, 2019. http://dx.doi.org/10.1109/ieeeconf44664.2019.9048771.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Peng, Guanze, and Quanyan Zhu. "Sequential Hypothesis Testing Game." In 2020 54th Annual Conference on Information Sciences and Systems (CISS). IEEE, 2020. http://dx.doi.org/10.1109/ciss48834.2020.1570617162.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Chang, Meng-Che, and Matthieu R. Bloch. "Evasive Active Hypothesis Testing." In 2020 IEEE International Symposium on Information Theory (ISIT). IEEE, 2020. http://dx.doi.org/10.1109/isit44484.2020.9174021.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Varshney, Kush R., and Lav R. Varshney. "Multilevel minimax hypothesis testing." In 2011 IEEE Statistical Signal Processing Workshop (SSP). IEEE, 2011. http://dx.doi.org/10.1109/ssp.2011.5967633.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Pericliev, Vladimir, and Ilarion Ilarionov. "Testing the projectivity hypothesis." In the 11th coference. Morristown, NJ, USA: Association for Computational Linguistics, 1986. http://dx.doi.org/10.3115/991365.991380.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Pattanayak, Kunal, Vikram Krishnamurthy, and Erik Blasch. "Inverse Sequential Hypothesis Testing." In 2020 IEEE 23rd International Conference on Information Fusion (FUSION). IEEE, 2020. http://dx.doi.org/10.23919/fusion45008.2020.9190339.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Farokhi, Farhad. "Non-Stochastic Hypothesis Testing with Application to Privacy Against Hypothesis-Testing Adversaries." In 2019 IEEE 58th Conference on Decision and Control (CDC). IEEE, 2019. http://dx.doi.org/10.1109/cdc40024.2019.9029652.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Reports on the topic "Testing hypothesis"

1

Andrews, Stephen A., and David E. Sigeti. Bayesian Hypothesis Testing. Office of Scientific and Technical Information (OSTI), November 2017. http://dx.doi.org/10.2172/1409741.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Al-Ibrahim, Mohammad M., and Pramod K. Varshney. On Disturbed Sequential Hypothesis Testing. Fort Belvoir, VA: Defense Technical Information Center, June 1991. http://dx.doi.org/10.21236/ada238691.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Bhatt, Nikita. Hypothesis testing and population sampling. BJUI Knowledge, January 2021. http://dx.doi.org/10.18591/bjuik.0743.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

List, John, Azeem Shaikh, and Yang Xu. Multiple Hypothesis Testing in Experimental Economics. Cambridge, MA: National Bureau of Economic Research, January 2016. http://dx.doi.org/10.3386/w21875.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Durlauf, Steven. Spectral Based Testing of the Martingale Hypothesis. Cambridge, MA: National Bureau of Economic Research, April 1992. http://dx.doi.org/10.3386/t0090.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Chair, Zelneddine, and Pramod K. Varshney. On Hypothesis Testing in Distributed Sensor Networks. Fort Belvoir, VA: Defense Technical Information Center, November 1987. http://dx.doi.org/10.21236/ada195910.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Levinsohn, James. Testing the Imports-as-Market-Discipline Hypothesis. Cambridge, MA: National Bureau of Economic Research, March 1991. http://dx.doi.org/10.3386/w3657.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Papastavrou, Jason D., Javed Pothiawala, and Michael Athans. Designing an Organization in a Hypothesis Testing Framework. Fort Belvoir, VA: Defense Technical Information Center, June 1989. http://dx.doi.org/10.21236/ada210443.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Zimmerman, Laura A., Drew A. Leins, Jessica Marcon, Ron Mueller, Singer T. Singer, and Christopher L. Vowels. Assessing Threat Detection Scenarios through Hypothesis Generation and Testing. Fort Belvoir, VA: Defense Technical Information Center, December 2015. http://dx.doi.org/10.21236/ad1002692.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Thornton, Daniel L. Testing the Expectations Hypothesis: Some New Evidence for Japan. Federal Reserve Bank of St. Louis, 2003. http://dx.doi.org/10.20955/wp.2003.033.

Full text
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Testing hypothesis' for particular source types:
Journal articles Dissertations / Theses Books
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography