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# Topic: Self-sufficiency

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###### In the News (Mon 19 Aug 19)

 Sufficient and Necessary Statistics, W van der Linden The property of sufficiency becomes interesting only if we are able to reduce the number of response vectors, combining them into a statistic without losing any information about the parameters. The other day, in a statistical textbook by Casella and Berger (1990) that is now my latest favorite, I found a reference to a paper by Dynkin (1951) that gives an answer to the question: "Are there any necessary statistics?" Dynkin defines a statistic as "necessary", if it is a function of every sufficient statistic. Necessary and sufficient statistics for a family of probability distributions. www.rasch.org /rmt/rmt63d.htm   (431 words)

 IUPUI Department of Mathematical Sciences - Course Information Sufficiency and completeness, the exponential family of distributions, theory of point estimation, Cramer-Rao inequality, Rao-Blackwell theorem with applications, maximum likelihood estimation, asymptotic distributions of ML estimators, hypothesis testing, Neyman-Pearson lemma, UMP tests, generalized likelihood ratio test, asymptotic distribution of the GLR test, sequential probability ratio test. Sufficiency and completeness, the exponential family of distributions, theory of point estimation, Cramer-Rao inequality, Rao-Blackwell Theorem with applications, maximum likelihood estimation, asymptotic distributions of ML estimators, hypothesis testing, Neyman-Pearson Lemma, UMP tests, generalized likelihood ratio test, asymptotic distribution of the GLR test, sequential probability ratio test. Descriptive statistics; elementary probability; random variables and their distributions; expectation; normal, binomial, Poisson, and hypergeometric distributions; sampling distributions; estimation and testing of hypotheses; one-way analysis of variance; correlation and regression. www.math.iupui.edu /programs/courses/stat.html   (1711 words)

 Sufficiency (statistics) A statistic T(X) is sufficient for θ precisely if the conditional probability distribution of the data X given the statistic '\'T(X'') does not depend on θ. A statistic that does that is called a sufficient statistic. In statistics, one often considers a family of probability distributions for a random variable www.sciencedaily.com /encyclopedia/sufficiency__statistics_   (548 words)

 Sufficient, Complete and Ancillary Statistics Sufficiency is related to several of the methods of constructing estimators that we have studied. Show that the sufficient statistics given above for the Bernoulli, Poisson, normal, gamma, and beta families are minimally sufficient for the given parameters. Thus, the notion of an ancillary statistic is complementary to the notion of a sufficient statistics (which contains all information about the parameter that is contained in the sample). www.ds.unifi.it /VL/VL_EN/point/point6.html   (675 words)

 corr2data.hlp The purpose of this is to allow you to perform analyses from summary statistics when summary statistics are all you know and summary statistics are sufficient to obtain results. For example, summary statistics are sufficient for performing t-tests, anova, principal components, regression, and factor analyses. If the statistical results differ beyond what is attributable to roundoff error, then use of {cmd:corr2data} is inappropriate. www.stata.com /updates3/ado.old/corr2data.hlp   (940 words)

 Self sufficient 'ish', the urban guide to almost self sufficiency. Selfsufficientish.com by Dave and Andy Hamilton Sites self sufficient 'ish' find useful - If you want to feature us and also see more self sufficiency sites and others that we like have a look here. Self sufficient 'ish's vegetable of the month this month is sweetcorn. Self sufficient 'ish' (Dave and Andy Hamilton) are not liable or responsible for what anyone does with the information that they find on any of our pages. www.selfsufficientish.com   (1073 words)

 UT Department of Statistics Graduate Courses Statistical computing, numerical methods for linear models and generalized linear models, nonlinear statistical methods, matrix computations and special matrices, essentials of Monte Carlo simulation, and resampling techniques. Prereq: 2 courses in statistics and consent of the statistics department director of graduate studies. Prereq: 4 courses in graduate-level statistics or consent of statistics department director of graduate studies. bus.utk.edu /stat/ms/gradcourses.html   (1173 words)

 AD-trees: Cached Sufficient Statistics for fast Counting and Data Mining queries on Massive Sky Surveys More importantly, many statistical operations are based on performing a large number of counts: for example there are many correlation measures based on taking a matrix of counts and performing certain significance tests on rows and columns of the matrices. More advanced statistical operations involve aggresive searches to find which subsets of attributes (also known as fields of the database) are most predictive of which other subsets., and most do many thousands of these correlations, which in turn involve dozens of counts. There are devastating computational and statistical difficulties; manual analysis of such data sources is now passing from being simply tedious into a new, fundamentally impossible realm where the data sources are just too large to assimilate by humans. www.cfht.hawaii.edu /ADASS/Abstracts/P1.13   (1341 words)

 Department of Statistics - Texas A&M University Statistical theories pertinent to solution of engineering problems in reliability introduced, established, and applied; distribution and failure theory including exponential, log normal, gamma, and Weibull; parameters studied include mean time to failure, failure rate, variances, and standard deviations, confidence limits, and tests of hypotheses. Transformations of statistics; statistical functionals including influence curves and M, L, and R estimators; asymptotic properties of estimators; asymptotic properties of tests; U-statistics; Edgeworth expansions and the bootstrap. Introduction to probability, probability distributions, and statistical inference; hypotheses testing using t and F tests; introduction to methods of analysis such as tests of independence, regression, analysis of variance with some consideration of planned experimentation. stat.tamu.edu /page.php?graduate_course_descriptions   (1414 words)

 JOHN SEYMOUR - born 12 June, 1914 died 14 September, 2004 Dorling and Kindersley continued their relationship with John and in 2002 produced The New Complete Book of Self Sufficiency which, as the dust jacket says, is the definitive guide for dreamers and realists. John describes their early struggles for self sufficiency in what became one his most popular books The Fat of the Land. John is best known as the author of The Complete Book of Self Sufficiency, first published in 1975. www.self-sufficiency.net   (1008 words)

 Self-Sufficiency Key Self- sufficiency during the Great Depression also meant the farmers had to deny themselves luxuries like automobiles; farmers did not have to worry about spending money on maintenance and fuel, except for farm equipment. Self- Sufficiency Key to Farmers' Survival During Depression It is commonly known that the Great Depression was rough on every class and life style in the United States. www.epcc.edu /ftp/Homes/monicaw/borderlands/12_self_sufficiency.htm   (973 words)

 G. (L.) v. B. (G.), 1995 CanLII 65 (S.C.C.) Once the sufficiency of a change has been established, the court must next determine the extent of the variation and to do so it generally has to make an assessment of the entirety of the present circumstances of the parties. Nonetheless, the threshold test cannot be applied properly unless the sufficiency of the change in circumstances is evaluated against the backdrop of the particular facts of the case at hand. Once a sufficient change that will justify variation has been identified, the court must next determine the extent to which it will reconsider the circumstances underlying, and the basis for, the support order itself. www.canlii.org /ca/cas/scc/1995/1995scc74.html   (9531 words)

 List of selected publications of Tom Snijders As an elaboration and practical implementation of this point, a statistical model for the dynamics of networks, expressed as digraphs with a fixed vertex set, is proposed in which the outdegree distribution is governed by parameters that are not connected to the parameters for the structural dynamics. A statistical approach to a posteriori blockmodeling for graphs is proposed.The model assumes that the vertices of the graph are partitioned into two unknown blocks and that the probability of an edge between two vertices depends only on the blocks to which they belong. Statistical procedures are derived for estimating the probabilities of edges and for predicting the block structure from observations of the edge pattern only. stat.gamma.rug.nl /snijders/publ.htm   (11082 words)

 hist.html The advantage was that the dimension of the sufficient statistics for the individual binary tests are lower in dimension than the dimension of any common feature set. Subsequently, Kay [kay2000] showed that simple sufficient statistics can exist for the binary tests even if no common sufficient statistic exists for differentiating the two classes. The method of VanTrees was all or nothing: either you have the raw data or you have a single scalar sufficient statistic: the likelihood ratio. www.npt.nuwc.navy.mil /csf/hist.html   (675 words)

 Sufficient Statistics Further examples of sufficient statistics may be found in the module on the Fisher-Neyman Factorization Theorem. Minimal sufficient statistics are, roughly speaking, sufficient statistics that cannot be compressed any more without losing information about the unknown parameter. Fortunately, spotting sufficient statistics can be made easier by the Fisher-Neyman Factorization Theorem. cnx.rice.edu /content/m11481/latest   (693 words)

 VFML: ExampleGroupStats.h File Reference Tracks and maintains the sufficient statistics needed to calculate Entropy and Gini of discrete and continuous attributes, as well as make some queries about the probability of events in the data. Creates a structure to track the statistics needed to cacluate several common machine metrics for the attributes that are active in the AttributeTracker. Frees all the memory that was being used by the structure. www.cs.washington.edu /dm/vfml/ExampleGroupStats_8h.html   (1531 words)

 bd-suft-seq.txt The sufficient statistic for such a class is minimal sufficient, and under the Jacobian condition described above, it may be used as the state vector in a minimal-dimension realization of the sufficient sequence. This statistic is also necessary in the sense of Dynkin [41, as noted by Arato 151; hence it is a minimal sufficient statistic, meaning that it is a function of every other sufficient statistic. Informally, we assume that the sufficient sequence may be generated as the output of a discrete-time system whose input is the sequence of ob- served random variables. www.math.rutgers.edu /pub/sontag/bd-suft-seq.txt   (5099 words)

 Statistics (STAT) - Course Descriptions - University Catalog 2005-06: George Mason University Statistical methods essential to the analysis of rates and proportions from data associated with clinical trials, case-control, prospective and cross-sectional studies in the health care sector. Topics include descriptive statistics, probability, distributions, sampling, inference, estimation and hypothesis testing; linear regression and correlation; the analysis of variance; multiple regression; and the analysis of association between categorical variables. Topics include limiting distributions and stochastic convergence, sufficient statistics, exponential families, statistical decision theory and opti-mality for point estimation, Bayesian methods, maximum likelihood, asymptotic results, interval estimation, optimal tests of statistical hypotheses, and likelihood ratio tests. www.gmu.edu /catalog/courses/stat.html   (3032 words)

 Title page for ETD etd-92297-162126 A statistic that summarizes an entire data set without losing any information about the family of distributions or the model is often called a sufficient statistic. Several card-counting statistics are compared by the amount of information each provides in discriminating between different deck compositions as compared to a sufficient statistic. The new method is used to evaluate the expected efficiency of a statistic in discriminating between any two values of the parameter as compared to a sufficient statistic. scholar.lib.vt.edu /theses/available/etd-92297-162126   (296 words)

 Course Descriptions for Mathematics and Statistics Statistical methods are taught with the aim of utilizing the SAS programs to arrive at outputs and their interpretation. The statistical software package Minitab will be used to reinforce these principles and to introduce students to the use of the computer in statistical analysis. A study of the multivariate normal distribution, statistical inference on multivariate data, multivariate analysis of covariance, canonical correlation, principal component analysis and cluster analysis. www.rit.edu /~932www/ugrad_bulletin/courses/cos/maths.html   (4239 words)

 EE126 Commentaries 9: Jean Walrand Assume that T(X)  is a sufficient statistic for (estimating) q. In this case, we say that T(X)  is a sufficient statistic for (estimating) q. For instance, if q is the unknown mean of (given q) i.i.d. robotics.eecs.berkeley.edu /~wlr/126/w9.htm   (578 words)

 Massachusetts Society for the Prevention of Cruelty to Children - Self Sufficiency Test By approving legislation to establish a self sufficiency standard that more accurately reflects the costs of living in the commonwealth, this committee and the General Court would take an important step toward ensuring the well-being of some of our most vulnerable residents. MSPCC recognizes that there are many other barriers to work and self sufficiency, including domestic violence, substance abuse and mental health disorders. The legislation before you would create the Commonwealth Corporation to develop a self sufficiency standard for Massachusetts. www.mspcc.org /index.cfm/fuseaction/Page.viewPage/pageId/169   (270 words)

 Self Sufficiency Trust Updates The Self Sufficiency Trust of Montana is a unique partnership between private and public sectors. To participate in the Self Sufficiency Trust, a donor (parent, family member, or other interested individual) establishes a trust account for the person with disabilities. ’s Self Sufficiency Trust (MSST) as a mechanism for families and friend of persons with disabilities to set aside funds to purchase supplemental services for persons with disabilities without jeopardizing their government benefits (Sections 53-18-101 through 105, MCA, http://data.opi.state.mt.us/bills/MCA/53/18/53-18-101.htm). www.pluk.org /sst.htm   (7859 words)

 Self Sufficiency Help Groups We offer anyone interested in self sufficiency help groups three services: tips on how to discover self sufficiency help groups information on the net, gratifying articles related to dating and recommendations to websites where you can purchase dating supplies and products. To locate the facts and info you're seeking to discover on self sufficiency help groups, it is important to execute your self sufficiency help groups information search logically. We offer users valuable tips for improving your self sufficiency help groups search results, along with an extensive search engine tutorial that will guide you in discovering the specific self sufficiency help groups information you desire. www.person-2-person.com /self_sufficiency_help_groups.html   (436 words)

 Project Self Sufficiency The mission of Project Self-Sufficiency / Family Self Sufficiency is to assist single parents and two-parent families in obtaining the education, skills and abilities necessary to move toward self-sufficiency. bcn.boulder.co.us /pss   (37 words)

 STAT 713 - Mathematical Statistics II STAT 713 - Mathematical Statistics II 713—Mathematical Statistics II (3) (Prereq: STAT 712) Further development of estimation theory and tests of hypotheses, including an introduction to Bayesian estimation, sufficiency, minimum variance principles, uniformly most powerful and likelihood ratio tests, and sequential probability ratio tests. To provide a foundation for further study in statistical theory at both the master's and doctoral levels. Purpose: To acquaint beginning graduate students in statistics and other disciplines with the mathematical development of statistical inference. www.stat.sc.edu /curricula/courses/713   (203 words)

 PSY 490 Debriefing Were the skills and knowledge from the courses you completed for the major, including statistics and methods, sufficient for preparing your proposal? www.mercer.edu /psychology/PSY490/PSY_490_Debriefing_Q06.htm   (52 words)

 Connexions - Content - Search Repository This module describes the various ways the term "statistics" is used. Learn what descriptive statistics are and see several applications of them. In order to find a solution to the basic reqursion equations, the scaling filter must satisfy a set of sufficient conditions. cnx.rice.edu /content/search?words=sufficient+statistic   (104 words)

 On Discrete Sufficient Statistics for Asynchronous Band-limited CDMA Systems - Mantravadi, Veeravalli (ResearchIndex) In most analyses of CDMA systems, the derivation of discrete sufficient statistics is facilitated by first relaxing the bandwidth constraints on the noise and the signaling waveforms in the corresponding continuoustime system model. Abstract: The problem of generating discrete sufficient statistics for statistical signal processing in Code Division Multiple Access (CDMA) systems is considered in context of the underlying channel bandwidth restrictions. On discrete sufficient statistics for asynchronous band-limited CDMA systems. citeseer.lcs.mit.edu /mantravadi98discrete.html   (588 words)

 Statistics Courses Statistical software SAS will be used throughout the course to demonstrate how to apply the techniques on real data. The topics include simple and multiple linear regression, matrix representation of the regression model, statistical inferences for regression model, diagnostics and remedies for multicollinearity, outlier and influential cases, polynomial regression and interaction regression models, model selection, weighted least square procedure for unequal error variances, and ANOVA model and test. This course presents regression analysis and related techniques, and is recommended for students throughout the natural and social sciences who are interested in applying regression analysis in their research and/or understanding the statistical concepts underlying the methodology. www.stat.unc.edu /courses.html   (1271 words)

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