Results 211 to 220 of about 538,044 (257)

Relationships between Linear Statistical Models

British Journal of Mathematics & Computer Science, 2015
To study the relationship between the linear statistical models we used methods of linear algebra, Hilbert spaces and statistics. It was found that there is a linear relationship between linear statistical models which is expressed by a matrix equality.
Vladimir Panov, Anatoly Varaksin
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Statistics: general linear models (a flexible approach)

Journal of Small Animal Practice, 2014
This article moves on to discuss a type of statistical testing different from those we have discussed previously, namely a General Linear Model. This system incorporates a number of other statistical models and is a powerful tool used widely in modern statistics.
M, Scott, D, Flaherty, J, Currall
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Random weightingT-statistics in linear regression models

Acta Mathematica Sinica, 1995
Summary: We have constructed a random weighting statistic to approximate the distribution of the Studentized least square estimator in a linear regresion model with ideal accuracy \(o(n^{- 1/2})\). Thus, we have provided a more practical distribution approximation method.
Shi, Jian, Zheng, Zhongguo
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Statistical tests as linear models

2022
This chapter examines the R implementations of statistical tests commonly taught in introductory statistics courses. Statistical tests have been developed by different people at different times. Such tests include the t-test and the Analysis of Variance (ANOVA).
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Statistical Analysis and Linear Models

2020
In Chapter 3, we explored the graph and map tasks. In Chapter 4, we will explore statistics and linear models.
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Statistical Inference in Linear Models

Technometrics, 1988
Statistical problems in modelling causal relationships estimating linear parameters estimating linear parameters using additional information admissibility and improvements of the generalized least squares estimator testing linear hypotheses confidence regions for linear parameters and regression functions Bayesian methods and structural inference ...
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Bivariate Statistics and Linear Models

2010
So far we’ve been studying univariate statistics; for example, for each individual in a population, we take a single measurement, height, age, etc. We combine these into a sample and compute a statistic: mean, variance, or some function of the variance. Now we consider the scenario where, for each individual in a population, we have two values: age and
Shravan Vasishth, Michael Broe
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A linear model of intermediate statistics

Journal of Physics A: Mathematical and General, 1997
Approximate Hamiltonians for the one-dimensional Calogero and two-dimensional anyon models in a harmonic well are constructed. In both models the particles interpolate between bosons and fermions. The article focuses on the remarkable properties of the solution of the Calogero model to first order in perturbation theory.
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Reformulating Classical Linear Statistical Models

1988
The problematic points in Chapter 1 can be reduced to a single issue, namely that inferential problems arise when statistical analyses are carried out on spatial data series having dependent observations. As Chapter 2 has suggested, this is a more trouble-some issue than its counterpart found in time series, because spatial interdependencies are both ...
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Integrative oncology: Addressing the global challenges of cancer prevention and treatment

Ca-A Cancer Journal for Clinicians, 2022
Jun J Mao,, Msce, Lorenzo Cohen, Karen M Mustian   +2 more
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