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Independent variables
"... ESE & Modeling 1 Development and continual improvement of empiricalevidencebased software models. 2 Capitalization organization wide of the results. 3 ICEIS 2002, Ciudad Real, April 4th © UniRoma2 – DISP – ESEG Giovanni Cantone Basic components ..."
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ESE & Modeling 1 Development and continual improvement of empiricalevidencebased software models. 2 Capitalization organization wide of the results. 3 ICEIS 2002, Ciudad Real, April 4th © UniRoma2 – DISP – ESEG Giovanni Cantone Basic components
Hamiltonian with z as the Independent Variable
"... Deduce the form of the Hamiltonian when z rather than t is considered to be the independent variable. Illustrate this for the case of a particle of charge q and mass m in an external electromagnetic field. ..."
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Cited by 3 (3 self)
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Deduce the form of the Hamiltonian when z rather than t is considered to be the independent variable. Illustrate this for the case of a particle of charge q and mass m in an external electromagnetic field.
Independent Variable Group Analysis
 in International Conference on Artificial Neural Networks  ICANN 2001, Georg Dorffner
, 2001
"... When modeling large problems with limited representational resources, it is important to be able to construct compact models of the data. Structuring the problem into subproblems that can be modeled independently is a means for achieving compactness. In this article we introduce Independent Variabl ..."
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Cited by 7 (3 self)
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with VQ. Experimental results are presented to show that variables are grouped according to statistical independence, and that a more compact model ensues due to the algorithm.
HOW TO CHOOSE THE INDEPENDENT VARIABLE?
"... A case study is presented, where the paper and pencil environment and the technological one are combined together and designed to face a subtle mathematical problem: how to choose the dependent Vs independent variables in modelling situations? We show how the combined approach allows to pose the pro ..."
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A case study is presented, where the paper and pencil environment and the technological one are combined together and designed to face a subtle mathematical problem: how to choose the dependent Vs independent variables in modelling situations? We show how the combined approach allows to pose
High dimensional graphs and variable selection with the Lasso
 ANNALS OF STATISTICS
, 2006
"... The pattern of zero entries in the inverse covariance matrix of a multivariate normal distribution corresponds to conditional independence restrictions between variables. Covariance selection aims at estimating those structural zeros from data. We show that neighborhood selection with the Lasso is a ..."
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Cited by 716 (22 self)
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The pattern of zero entries in the inverse covariance matrix of a multivariate normal distribution corresponds to conditional independence restrictions between variables. Covariance selection aims at estimating those structural zeros from data. We show that neighborhood selection with the Lasso
PROBABILITY INEQUALITIES FOR SUMS OF BOUNDED RANDOM VARIABLES
, 1962
"... Upper bounds are derived for the probability that the sum S of n independent random variables exceeds its mean ES by a positive number nt. It is assumed that the range of each summand of S is bounded or bounded above. The bounds for Pr(SES> nt) depend only on the endpoints of the ranges of the s ..."
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Cited by 2171 (2 self)
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Upper bounds are derived for the probability that the sum S of n independent random variables exceeds its mean ES by a positive number nt. It is assumed that the range of each summand of S is bounded or bounded above. The bounds for Pr(SES> nt) depend only on the endpoints of the ranges
Bayesian Model Selection in Social Research (with Discussion by Andrew Gelman & Donald B. Rubin, and Robert M. Hauser, and a Rejoinder)
 SOCIOLOGICAL METHODOLOGY 1995, EDITED BY PETER V. MARSDEN, CAMBRIDGE,; MASS.: BLACKWELLS.
, 1995
"... It is argued that Pvalues and the tests based upon them give unsatisfactory results, especially in large samples. It is shown that, in regression, when there are many candidate independent variables, standard variable selection procedures can give very misleading results. Also, by selecting a singl ..."
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Cited by 554 (21 self)
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It is argued that Pvalues and the tests based upon them give unsatisfactory results, especially in large samples. It is shown that, in regression, when there are many candidate independent variables, standard variable selection procedures can give very misleading results. Also, by selecting a
VERY HIGH RESOLUTION INTERPOLATED CLIMATE SURFACES FOR GLOBAL LAND AREAS
, 2005
"... We developed interpolated climate surfaces for global land areas (excluding Antarctica) at a spatial resolution of 30 arc s (often referred to as 1km spatial resolution). The climate elements considered were monthly precipitation and mean, minimum, and maximum temperature. Input data were gathered ..."
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Cited by 516 (8 self)
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from a variety of sources and, where possible, were restricted to records from the 1950–2000 period. We used the thinplate smoothing spline algorithm implemented in the ANUSPLIN package for interpolation, using latitude, longitude, and elevation as independent variables. We quantified uncertainty
Agglomerative Independent Variable Group Analysis
"... Independent Variable Group Analysis (IVGA) is a method for grouping dependent variables together while keeping mutually independent or weakly dependent variables in separate groups. In this paper two variants of an agglomerative method for learning a hierarchy of IVGA groupings are presented. The me ..."
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Independent Variable Group Analysis (IVGA) is a method for grouping dependent variables together while keeping mutually independent or weakly dependent variables in separate groups. In this paper two variants of an agglomerative method for learning a hierarchy of IVGA groupings are presented
Results 1  10
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