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Best Linear Unbiased Prediction
In statistics, best linear unbiased prediction (BLUP) is used in linear mixed models for the estimation of random effects. BLUP was derived by Charles Roy Henderson in 1950 but the term "best linear unbiased predictor" (or "prediction") seems not to have been used until 1962. "Best linear unbiased predictions" (BLUPs) of random effects are similar to best linear unbiased estimates (BLUEs) (see Gauss–Markov theorem) of fixed effects. The distinction arises because it is conventional to talk not about ''estimating'' fixed effects but rather about ''predicting'' random effects, but the two terms are otherwise equivalent. (This is a bit strange since the random effects have already been "realized"; they already exist. The use of the term "prediction" may be because in the field of animal breeding in which Henderson worked, the random effects were usually genetic merit, which could be used to predict the quality of offspring (Robinson page 28)). However, the equations for the "fixed" ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Statistics
Statistics (from German language, German: ''wikt:Statistik#German, Statistik'', "description of a State (polity), state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model to be studied. Populations can be diverse groups of people or objects such as "all people living in a country" or "every atom composing a crystal". Statistics deals with every aspect of data, including the planning of data collection in terms of the design of statistical survey, surveys and experimental design, experiments.Dodge, Y. (2006) ''The Oxford Dictionary of Statistical Terms'', Oxford University Press. When census data cannot be collected, statisticians collect data by developing specific experiment designs and survey sample (statistics), samples. Representative sampling as ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Index Selection
Index selection is a method of artificial selection Selective breeding (also called artificial selection) is the process by which humans use animal breeding and plant breeding to selectively develop particular phenotypic traits (characteristics) by choosing which typically animal or plant m ... in which several useful traits are selected simultaneously. First, each trait that is going to be selected is assigned a weight – the importance of the trait. I.e., if you were selecting for both height and the coat darkness in dogs, if height were the more important of the two one would assign that a higher weighting. For instance, height's weighting could be ten and coat darkness could be one. This weighting value is then multiplied by the observed value in each individual animal and then the score for each of the characteristics is summed for each individual. This result is the index score and can be used to compare the worth of each organism being selected. Therefore, only those ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Biometrics (journal)
''Biometrics'' is a journal that publishes articles on the application of statistics and mathematics to the biological sciences. It is published by the International Biometric Society (IBS).Biometrics homepage Originally published in 1945 under the title ''Biometrics Bulletin'', the journal adopted the shorter title in 1947. Biometrics, Vol. 3, No. 1, Mar., 1947 Page 53 /ref> A notable contributor to the journal was , for whom a memorial edition was published in 1964. [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Minimum Mean Square Error
In statistics and signal processing, a minimum mean square error (MMSE) estimator is an estimation method which minimizes the mean square error (MSE), which is a common measure of estimator quality, of the fitted values of a dependent variable. In the Bayesian setting, the term MMSE more specifically refers to estimation with quadratic loss function. In such case, the MMSE estimator is given by the posterior mean of the parameter to be estimated. Since the posterior mean is cumbersome to calculate, the form of the MMSE estimator is usually constrained to be within a certain class of functions. Linear MMSE estimators are a popular choice since they are easy to use, easy to calculate, and very versatile. It has given rise to many popular estimators such as the Wiener–Kolmogorov filter and Kalman filter. Motivation The term MMSE more specifically refers to estimation in a Bayesian setting with quadratic cost function. The basic idea behind the Bayesian approach to estimation stems ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Kriging
In statistics, originally in geostatistics, kriging or Kriging, also known as Gaussian process regression, is a method of interpolation based on Gaussian process governed by prior covariances. Under suitable assumptions of the prior, kriging gives the best linear unbiased prediction (BLUP) at unsampled locations. Interpolating methods based on other criteria such as smoothness (e.g., smoothing spline) may not yield the BLUP. The method is widely used in the domain of spatial analysis and computer experiments. The technique is also known as Wiener–Kolmogorov prediction, after Norbert Wiener and Andrey Kolmogorov. The theoretical basis for the method was developed by the French mathematician Georges Matheron in 1960, based on the master's thesis of Danie G. Krige, the pioneering plotter of distance-weighted average gold grades at the Witwatersrand reef complex in South Africa. Krige sought to estimate the most likely distribution of gold based on samples from a few boreholes. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Holstein Friesian Cattle
Holstein Friesians (often shortened to Holsteins in North America, while the term Friesians is often used in the UK and Ireland) are a breed of dairy cattle that originated in the Netherlands, Dutch provinces of North Holland and Friesland, and Schleswig-Holstein in Northern Germany. They are known as the world's highest-producing dairy animals. Dutch people, Dutch and Germans, German breeders developed the breed with the goal of producing animals that could most efficiently use grass, the area's most abundant resource, as their food. Over the centuries, the result was a high-producing, black-and-white Dairy cattle, dairy cow. The Holstein-Friesian is the most widespread cattle breed in the world; it is found in more than 150 countries. With the growth of the New World, a demand for milk developed in North America and South America, and dairy breeders in those regions at first imported their livestock from the Netherlands. However, after about 8,800 Friesians (German Black Pied c ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
University Of Guelph
, mottoeng = "to learn the reasons of realities" , established = May 8, 1964 ()As constituents: OAC: (1874) Macdonald Institute: (1903) OVC: (1922) , type = Public university , chancellor = Mary Anne Chambers (not yet installed) , president = Charlotte A.B. Yates , city = Guelph, Ontario , country = Canada , students = 29,923 , undergrad = 23,926 , postgrad = 3,035 , faculty = 830 , administrative_staff = 3,100 , campus = Urban , athletics_affiliations = CIS, OUA , sports_nickname = Gryphons , colours = , , affiliations = AUCC, CARL, IAU, COU, CIS, CUSID, Fields Institute, OUA, Ontario Network of Women in engineering, CBIE , endowment = CA$418 million (2021) , website = , logo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Estimated Breeding Value
Estimation (or estimating) is the process of finding an estimate or approximation, which is a value that is usable for some purpose even if input data may be incomplete, uncertain, or unstable. The value is nonetheless usable because it is derived from the best information available.C. Lon Enloe, Elizabeth Garnett, Jonathan Miles, ''Physical Science: What the Technology Professional Needs to Know'' (2000), p. 47. Typically, estimation involves "using the value of a statistic derived from a sample to estimate the value of a corresponding population parameter".Raymond A. Kent, "Estimation", ''Data Construction and Data Analysis for Survey Research'' (2001), p. 157. The sample provides information that can be projected, through various formal or informal processes, to determine a range most likely to describe the missing information. An estimate that turns out to be incorrect will be an overestimate if the estimate exceeds the actual result and an underestimate if the estimate fall ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Best Linear Unbiased Estimator
Best or The Best may refer to: People * Best (surname), people with the surname Best * Best (footballer, born 1968), retired Portuguese footballer Companies and organizations * Best & Co., an 1879–1971 clothing chain * Best Lock Corporation, a lock manufacturer * Best Manufacturing Company, a farm machinery company * Best Products, a chain of catalog showroom retail stores * Brihanmumbai Electric Supply and Transport, a public transport and utility provider * Best High School (other) Acronyms * Berkeley Earth Surface Temperature, a project to assess global temperature records * BEST Robotics, a student competition * BioEthanol for Sustainable Transport * Bootstrap error-adjusted single-sample technique, a statistical method * Bringing Examination and Search Together, a European Patent Office initiative * Bronx Environmental Stewardship Training, a program of the Sustainable South Bronx organization * Smart BEST, a Japanese experimental train * Brihanmumbai Electric ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Mixed Model
A mixed model, mixed-effects model or mixed error-component model is a statistical model containing both fixed effects and random effects. These models are useful in a wide variety of disciplines in the physical, biological and social sciences. They are particularly useful in settings where repeated measurements are made on the same statistical units (longitudinal study), or where measurements are made on clusters of related statistical units. Because of their advantage in dealing with missing values, mixed effects models are often preferred over more traditional approaches such as repeated measures analysis of variance. This page will discuss mainly linear mixed-effects models (LMEM) rather than generalized linear mixed models or nonlinear mixed-effects models. History and current status Ronald Fisher introduced random effects models to study the correlations of trait values between relatives. In the 1950s, Charles Roy Henderson provided best linear unbiased estimates of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dependent And Independent Variables
Dependent and independent variables are variables in mathematical modeling, statistical modeling and experimental sciences. Dependent variables receive this name because, in an experiment, their values are studied under the supposition or demand that they depend, by some law or rule (e.g., by a mathematical function), on the values of other variables. Independent variables, in turn, are not seen as depending on any other variable in the scope of the experiment in question. In this sense, some common independent variables are time, space, density, mass, fluid flow rate, and previous values of some observed value of interest (e.g. human population size) to predict future values (the dependent variable). Of the two, it is always the dependent variable whose variation is being studied, by altering inputs, also known as regressors in a statistical context. In an experiment, any variable that can be attributed a value without attributing a value to any other variable is called an in ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Empirical Bayes
Empirical Bayes methods are procedures for statistical inference in which the prior probability distribution is estimated from the data. This approach stands in contrast to standard Bayesian methods, for which the prior distribution is fixed before any data are observed. Despite this difference in perspective, empirical Bayes may be viewed as an approximation to a fully Bayesian treatment of a hierarchical model wherein the parameters at the highest level of the hierarchy are set to their most likely values, instead of being integrated out. Empirical Bayes, also known as maximum marginal likelihood, represents a convenient approach for setting hyperparameters, but has been mostly supplanted by fully Bayesian hierarchical analyses since the 2000s with the increasing availability of well-performing computation techniques. Introduction Empirical Bayes methods can be seen as an approximation to a fully Bayesian treatment of a hierarchical Bayes model. In, for example, a two-sta ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
