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Topic: Copula (statistics)

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	copula - Search Results - MSN Encarta
		In linguistics, a copula is a word used to link the subject of a sentence with a predicate (a subject complement or an adverbial).
		In statistics, a copula is a multivariate cumulative distribution function defined on the n-dimensional unit cube [0, 1] such that every marginal distribution is uniform on the interval [0, 1].
		Copula A copula is a special word that combines the subject of a sentence and its description.
	encarta.msn.com /copula.html (154 words)

	Copula (statistics) - Wikipedia, the free encyclopedia
		In statistics, a copula is a multivariate cumulative distribution function defined on the n-dimensional unit cube [0, 1]
		The copula contains all of the information on the nature of the dependence between the two random variables that can be given without the marginal distributions, but gives no information on the marginal distributions.
		For θ = 0 in the Clayton copula, the random variables are statistically independent.
	en.wikipedia.org /wiki/Copula_(statistics) (310 words)

	Category:Statistics - Wikipedia, the free encyclopedia
		Statistics is the science and practice of developing human knowledge through the use of empirical data.
		It is based on statistical theory which is a branch of applied mathematics.
		Because the aim of statistics is to produce the "best" information from available data, some authors make statistics a branch of decision theory.
	en.wikipedia.org /wiki/Category:Statistics (145 words)

	GloriaMundi Resource Detail page
		Copulas are functions that join multivariate distribution functions to their one-dimensional margins.
		The study of copulas and their role in statistics is a new but vigorously growing field.
		Copulas can be the appropriate tool to combine information in a non-Gaussian world and without restricting to the linear correlation coefficient since they are related to non-parametric measures of association.
	www.gloriamundi.org /resultstop10.asp?keyword=copula (2967 words)

	Search Results for 'List-of-statistical-topics' (Site not responding. Last check: 2007-11-04)
		The American Statistical Association (ASA) is a scientific and educational society in the United States with the stated mission to promote excellence in the application of statistical science across the wealth of human endeavor.
		Clarksville-Hopkinsville MSA The Clarksville-Hopkinsville metropolitan statistical area is a MSA that comprises of the cities of Clarksville, Montgomery County, Tennessee and Hopkinsville, Christian County, Kentucky.
		The population of the MSA increased from 189,279 in 1990 to 232,000 by the 2000 census.
	www.worldhistory.com /wiki/L/List-of-statistical-topics.htm (1107 words)

	[No title] (Site not responding. Last check: 2007-11-04)
		Copulas are % functions that describe dependencies among variables, and provide a way % to create distributions to model correlated multivariate data.
		The family of bivariate Gaussian copulas is parameterized by % Rho = [1 rho; rho 1], the linear correlation matrix.
		The choice of a particular copula in an application may be % based on actual observed data, or different copulas may be used as a way % of determining the sensitivity of simulation results to the input % distribution.
	www.clemson.edu /cle4_share/CWE/COES0915_CLUG/REFERENCE/matlabr14/toolbox/stats/copulademo.m (2077 words)

	Copula (Site not responding. Last check: 2007-11-04)
		In linguistics, a copula is a word that is used to link the subject of a sentence with a predicate (a subject complement or an adverbial).
		A copula is sometimes (though not always) a verb or a verb-like part of speech.
		The term copula is also used in mathematics to describe a mathematical operation that links a univariate distribution function to a multivariate distribution function.
	copula.ask.dyndns.dk (2083 words)

	Simulation of dependent random variables using copulas (Site not responding. Last check: 2007-11-04)
		Copulas are functions that describe dependencies among variables, and provide a way to create distributions to model correlated multivariate data.
		The family of bivariate Gaussian copulas is parameterized by Rho = [1 rho; rho 1], the linear correlation matrix.
		The choice of a particular copula in an application may be based on actual observed data, or different copulas may be used as a way of determining the sensitivity of simulation results to the input distribution.
	www.clemson.edu /cle4_share/CWE/COES0915_CLUG/REFERENCE/matlabr14/toolbox/stats/html/copulademo.html (2396 words)

	Wilmott Forums - puzzle?? Why copula?
		From a statistical viewpoint, however the selecting and estimation process are eased, since we can pick the marginal distribution function independently from each other and from the dependence structure.
		The use of a copula function introduces greater flexibility but it is an open question whether selecting a copula function is easier than selecting the multivariate distribution function directly.
		Read some papers that uses copula functions to value the credit derivatives, all of them use hazard rate in the simulation of default times and assumed that the hazard rate is constant throughout for all the obligors in a basket..
	www.wilmott.com /messageview.cfm?catid=8&threadid=25426 (2140 words)

	Copula: Encyclopedia topic (Site not responding. Last check: 2007-11-04)
		The word copula originates from the Latin (Latin: Any dialect of the language of ancient Rome) noun (noun: A word that can be used to refer to a person or place or thing) for a "link or tie" that connects two different things.
		A copula is sometimes (though not always) a verb (verb: A word that serves as the predicate of a sentence) or a verb-like part of speech.
		The term copula is also used in mathematics (mathematics: A science (or group of related sciences) dealing with the logic of quantity and shape and arrangement) to describe a mathematical operation that links a univariate distribution function (distribution function: more facts about this subject) to a multivariate distribution function.
	www.absoluteastronomy.com /reference/copula (2666 words)

	YRD abstracts
		Test statistics for the nonparametric hypotheses of no main effect, and no interaction effect which adjusts for the presence of a covariate, are obtained.
		There is a clear need for the identification of landmarks on the curve as part of the statistical analysis.
		Furthermore, several statistical approaches have been developed over the past ten years from a parametric, semi-parametric and non-parametric point of view.
	www.stat.ucl.ac.be /YRD/YRD1/abstracts.html (1570 words)

	3 PUBLICATIONS AND EDITING ACTIVITIES
		In our case, two copulas are used to obtain a parametric form for the joint density of the repeated responses and of the dropout indicators.
		Three copula families are used: the product copula, the copula of Frank (1979) and a copula generated from the standard multivariate normal distribution.
		A linear wavelet estimator of the density is considered and the test statistic is based on the resolution level, the discrete smoothing parameter of the estimate.
	www.stat.ucl.ac.be /ISrapport/rap01/rap2001/node4.html (6629 words)

	LUMC: Medical Statistics and Bioinformatics: Minisymposium
		Copulas (Sklar, 1959) enable to specify multivariate distributions with given marginals.
		They are characterized by their generator, a strictly decreasing convex function on (0,1) which tends to infinity at zero and which is zero at one.
		Parameters associated to parametric models for the marginals can be estimated jointly with the copula parameters.
	www.lumc.nl /3020/algemeen/Colloquia/ArchimedeanCopulaEstimation.html (290 words)

	Dr. Arsham's Statistics Site
		Statistical inference aims at determining whether any statistical significance can be attached that results after due allowance is made for any random variation as a source of error.
		Statistics is a science of making decisions with respect to the characteristics of a group of persons or objects on the basis of numerical information obtained from a randomly selected sample of the group.
		Almost all standard statistical analyses are conditioned on the assumption that the population is homogeneous, meaning that its density (for continuous random variables) or probability mass function (for discrete random variables) is unimodal.
	home.ubalt.edu /ntsbarsh/Business-stat/opre504.htm (12693 words)

	Abstract: Statistics Dept Seminars (Site not responding. Last check: 2007-11-04)
		distribution: a joint distribution is completely characterized by its copula function and the marginal distributions.
		Copulas can also be viewed as a distribution function on the unit cube with uniform marginals.
		independence, rank statistics, and parametric and semi-parametric models are considered as well.
	www.stat.yale.edu /seminars/PastSeminars/2001-02/Radulovic.html (169 words)

	Correlation - Psychology Central
		In probability theory and statistics, correlation, also called correlation coefficient, is a numeric measure of the strength of linear relationship between two random variables.
		Pearson's correlation coefficient is a parametric statistic, and it may be less useful if the underlying assumption of normality is violated.
		Non-parametric correlation methods, such as Spearman's ρ and Kendall's τ may be useful when distributions are not normal; they are a little less powerful than parametric methods if the assumptions underlying the latter are met, but are less likely to give distorted results when the assumptions fail.
	psychcentral.com /psypsych/Correlation (1029 words)

	Seminars 2005 - Abstracts - Department of Econometrics and Business Statistics
		Abstract: We introduce a general approach to nonlinear quantile regression modelling that is based on the identification of the copula function that completely defines the entire dependency structure between the variables of interest.
		Hence we extend Koenker and Bassett's [1978] original statement of the quantile regression problem by determining a distribution for the dependent variable Y conditional on the regressors X and hence the specification of the quantile regression functions.
		Some properties of the copula based quantiles or c-quantiles are then derived.
	www.buseco.monash.edu.au /depts/ebs/seminars/2005/3-11.php (233 words)

	Estimation of Copula Models for Time Series of Possibly Different Lengths
		The theory of conditional copulas provides a means of constructing flexible multivariate density models, allowing for time varying conditional densities of each individual variable, and for time-varying conditional dependence between the variables.
		Further, the use of copulas in constructing these models often allows for the partitioning of the parameter vector into elements relating only to a marginal distribution, and elements relating to the copula.
		We extend the existing statistics literature on the estimation of copula models to consider data that exhibit temporal dependence and heterogeneity.
	ideas.repec.org /p/cdl/ucsdec/2001-17.html (469 words)

	statistics
		A copula based statistical method for fitting joint cumulative returns between a market index and a single
		minimization of the bivariate chi-square statistic associated to an adequate bivariate version of the usual
		minimum distance statistics, is found to be superior to that of various "good" competitive models including
	www.geocities.com /hurlimann53/statistics.html (619 words)

	Wiley::Copula Methods in Finance
		2.3 Sklar’s theorem and the probabilistic interpretation of copulas.
		4.5 Density and canonical representation of a multidimensional copula.
		7.5.1 Derivation of a multivariate Clayton copula density.
	www.wiley.com /WileyCDA/WileyTitle/productCd-0470863447,descCd-tableOfContents.html (332 words)

	copula (statistics)
		copula (statistics) is one of the topics in focus at Global Oneness.
		In Chinese languages, both states and qualities are generally expressed with stative verbs with no need for a copula, e.g., "to be tired" (累 lèi), "to be hungry" (饿 è), "to be located at" (在 zài), "to be stupid" (笨 bèn) and so forth.
		We can identify several sub-uses of the copula: Identity: "I only want to be myself." "When the area behind the dam fills, it will be a lake." "The Morning Star is the Evening Star." "Boys will be boys." "I yam what I yam" (Popeye).
	www.experiencefestival.com /copula_statistics (632 words)

	Copula (statistics) (Site not responding. Last check: 2007-11-04)
		In statistics, a copula is a probability distribution on a unit cube [0, 1]
		The copula contains all of the information on the nature of the dependence between the two random variables that can be given without the marginal distributions, but gives no information on the marginal distributions.
		In effect the information on the marginals and the information on the dependence are neatly separated from each other.
	www.alloffinance.com /Copula_%28statistics%29.html (606 words)

	[No title]
		My focus in recent years has been the statistical modeling of populations of neurons in the primary field (AI) of auditory cortex and how the neural firing patterns convey information about the spatial environment.
		A major challenge in the study of neural coding is identifying the role of coordinated activity between neurons.
		A second area of research, with the Human Brain Research Laboratory in the Department of Neurosurgery at the University of Iowa, investigates neural coding of speech at the level of auditory cortex in humans using direct electrophysiological recordings during auditory psychophysical tasks.
	wavelet.psych.wisc.edu /jenison.html (406 words)

	On association in a copula with time transformations -- Fine and Jiang 87 (3): 559 -- Biometrika
		Department of Statistics, University of Wisconsin, Madison, Wisconsin 53706, USA E-mail: fine@stat.wisc.edu; jiangh@stat.wisc.edu
		copula in which covariates are incorporated into the marginal
		A goodness-of-fit test for the assumed copula is presented and
	biomet.oxfordjournals.org /cgi/content/abstract/87/3/559 (154 words)

	Wang Colloquium
		A bivariate survivor function S(t_{1},t_{2}) is said to be generated by an archimedean copula if it can be expressed in the form S(t_{1},t_{2})=p[q{S_{1}(t_{1})}+q{S_{2}(t_{2})}] for some convex, decreasing function q defined on (0,1].
		Interestingly, our estimates based on the empirical V's are much more precise than the estimates based on the true and unknown V's.
		We also investigate an alternative procedure based on iteratively estimating the V's using the assumed copula structure.
	cams.njit.edu /Seminars/Spring2002/seminar_5_17_02.htm (193 words)

	[No title]
		In our SCOMDY specification, the copula function captures the concurrent dependence between the components of the multivariate innovation, while the marginal distributions characterize the behavior of individual components of the innovation.
		In the probability literature, the copula approach has mainly been used to generate (or simulate) various multivariate distributions with given marginals; In the statistics literature, the copula method has been widely used in survival analysis to model nonlinear correlations, see e.g.
		In order to overcome some statistical problems associated with the Riskmetrics approach (see Zaffaroni, P.(2003) for details) and, at the same time, to allow the multivariate GARCH to handle large scale applications, a number of approaches have recently been advanced in the literature.
	econweb.rutgers.edu /nswanson/papers/conf/conf_abstracts.doc (2742 words)

	Statistics.com: Encyclopedia of Biostatistics (Site not responding. Last check: 2007-11-04)
		Statistical analysts in the pharmaceutical industry, insurance companies, HMO’s, hospitals, medical schools, government regulators, public health agencies and the health care and health services sector generally should have access to this classic encyclopedia, which has just been updated with 182 new and 300 revised articles.
		Building on the widely acclaimed First Edition, the distinguished editorial team has commissioned new material and revised existing articles to ensure that the coverage of key topics is completely up to date and comprehensive.
		Statistical Methods in Medical Research (J) Teaching statistics to medical students
	www.statistics.com /content/encyclopedia/bioencyclopedia.html (322 words)

	Weak convergence of empirical copula processes, Jean-David Fermanian, Dragan Radulovic, Marten Wegkamp
		Weak convergence of the empirical copula process has been established by Deheuvels in the case of independent marginal distributions.
		We extend their results by proving the weak convergence of this process in $\ell^\infty([0,1]^2)$> under minimal conditions on the copula function, which coincides with the result obtained by Gaenssler and Stute.
		It is argued that the condition on the copula function is necessary.
	projecteuclid.org /Dienst/UI/1.0/Summarize/euclid.bj/1099579158 (647 words)

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