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Regularized Least Square Regression with Unbounded and Dependent Sampling
2013
Abstract and Applied Analysis
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The standard bound assumption for output data is abandoned and the learning algorithm is implemented with samples drawn from dependent sampling process with a more general output data condition. ...
This paper mainly focuses on the least square regression problem for the -mixing and -mixing processes. ...
It mainly studies the half supervised coefficient regularization with indefinite kernels and unbounded sampling, where the unbounded condition is ∫ 2 ≤̂2 for some constant̂> 0. ...
doi:10.1155/2013/139318
fatcat:ecz5g5bj4bcapoduyzpur3uvhy
An Extensive Examination of Regression Models with a Binary Outcome Variable
2017
Journal of the AIS
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We compare its performance to logit and probit under different sample sizes, error distributions, and more. ...
We find that coefficient directions, statistical significance, and marginal effects yield results similar to logit and probit. ...
We are grateful to the AE and the three reviewers for their helpful comments and suggestions that helped improve this paper. ...
doi:10.17705/1jais.00455
fatcat:psz3szwokfhn5bj6pzxmdylamq
Comparison of the modified unbounded penalty and the LASSO to select predictive genes of response to chemotherapy in breast cancer
2018
PLoS ONE
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Recently Lee and Oh developed a novel random-effect covariate selection method called the modified unbounded penalty (MUB) regression, whose penalization function can equal minus infinity at 0 in order ...
In practice the LASSO regression of Tibshirani, which penalizes the likelihood of the model by the L1 norm of the regression coefficients, has become the gold-standard to reach these objectives. ...
Wessels from the Netherlands Cancer Institute and Delft University of Technology for sharing the data used in this research paper as well as for its fruitful advice. ...
doi:10.1371/journal.pone.0204897
pmid:30273405
pmcid:PMC6166949
fatcat:o3vbkzn235euhdymwwrejntfpe
Learning Theory
2014
Abstract and Applied Analysis
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Acknowledgments The guest editors wish to express their sincere gratitude to the authors and reviewers who contributed greatly to the success of this special issue. ...
Cai investigated a coefficient-based least squares regression problem with indefinite kernels from nonidentical unbounded sampling processes, which extends the existing related results. W. Gao and T. ...
Chen and J. Wu, where they studied the ranking problem with L1-regularization associated with a convex loss. P. Ye and Y. ...
doi:10.1155/2014/138960
fatcat:xlgia2cr2ffcpkckizvf74tu4e
Coefficient-Based Regression with Non-Identical Unbounded Sampling
2013
Abstract and Applied Analysis
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We investigate a coefficient-based least squares regression problem with indefinite kernels from non-identical unbounded sampling processes. ...
Here non-identical unbounded sampling means the samples are drawn independently but not identically from unbounded sampling processes. ...
The work described in this paper is supported partially by National Natural Science Foundation of China (Grant no. 11001247) and Doctor Grants of Guangdong University of Business Studies (Grant no. 11BS11001 ...
doi:10.1155/2013/134727
fatcat:tdccsw6fsrerldlut6act7mvw4
Robust measures of association in the correlation model
1994
Statistics and Probability Letters
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In the correlation model, the classical coefficient of multiple determination J?' is a measure of association between the dependent random variable Y and the random vector of independent variables x. ...
In the regression model robust estimates of the regression coefficients are less sensitive to outlying points than least squares estimates. ...
McKean and Naranjo was partially supported by NSF Grant DMS-9103916. We appreciate the helpful comments from an anonymous referee. ...
doi:10.1016/0167-7152(94)90017-5
fatcat:iqdc2ritdbhxlkwuctqm5mmk2m
Contribution of the activities of CYP3A, CYP2D6, CYP1A2 and other potential covariates to the disposition of methadone in patients undergoing methadone maintenance treatment
2009
British Journal of Clinical Pharmacology
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CYP3A activity explained 22, 16, 15 and 23% of the variation in unbound (R)-, unbound (S)-, total (RS)-and total (S)-methadone clearances, respectively. ...
Population pharmacokinetics and subsequent multiple regression analysis were used to calculate methadone oral clearance and to identify its covariates. ...
As a drug with a low extraction ratio [17] , the hepatic clearance of methadone following intravenous (i.v.) administration is dependent on its unbound fraction and intrinsic clearance [13] . ...
doi:10.1111/j.1365-2125.2008.03312.x
pmid:19133059
pmcid:PMC2668081
fatcat:v5pex4rnefb4zh2t2kegrtorty
Rates of convergence of the Adaptive LASSO estimators to the Oracle distribution and higher order refinements by the bootstrap
2013
Annals of Statistics
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In this paper, we investigate the rate of convergence of the ALASSO estimator to the oracle distribution when the dimension of the regression parameters may grow to infinity with the sample size. ...
It is shown that the rate critically depends on the choices of the penalty parameter and the initial estimator, among other factors, and that confidence intervals (CIs) based on the oracle limit law often ...
We generated the variables (c i , ϵ i ) as iid bivariate normal vectors with zero mean vector and identity covariance matrix. The sample size considered was n = 200. ...
doi:10.1214/13-aos1106
fatcat:edoizpwjdrbt5jfho4hf62dwvi
Page 1997 of Mathematical Reviews Vol. , Issue 99c
[page]
1991
Mathematical Reviews
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When a LAU parameter or paramet- ric function has an unbounded range, it is shown under general regularity conditions that any valid confidence set with level | — a for this parameter must be unbounded ...
., IV regressions with poor instruments), it is observed that likelihood-based methods (e.g., likelihood-ratio tests and confidence sets) combined with projection techniques can easily yield valid tests ...
Page 8699 of Mathematical Reviews Vol. , Issue 99m
[page]
1999
Mathematical Reviews
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Summary: “We consider likelihood-based inference from multi- variate regression models with independent Student-¢ errors with unknown degrees of freedom. ...
Consider a linear regression model with regression parameter vec- tor # and a normally distributed error term. ...
Positive-shrinkage and Pretest Estimation in Multiple Regression: A Monte Carlo study with Applications
[article]
2011
arXiv
pre-print
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Performance of positive-shrinkage and pretest estimators are compared with unrestricted estimator under varying degree of uncertainty of the prior information. ...
Thus, pretest estimator chooses between the restricted and unrestricted estimators depending on the outcome of the preliminary test. ...
Ahmed (1997) gave a detailed description of shrinkage estimation, and discussed large sample estimation techniques in a regression model with non-normal errors. ...
arXiv:1109.2527v1
fatcat:aa7743b66nbpnfmnzmr66qihy4
Nonconcave Penalized Likelihood With NP-Dimensionality
2011
IEEE Transactions on Information Theory
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This fills a long-standing gap in the literature where the dimensionality is allowed to grow slowly with the sample size. ...
In this paper, we show that in the context of generalized linear models, such methods possess model selection consistency with oracle properties even for dimensionality of nonpolynomial (NP) order of sample ...
ACKNOWLEDGMENT We sincerely thank the Associate Editor and referee for their constructive comments that significantly improved the paper. ...
doi:10.1109/tit.2011.2158486
pmid:22287795
pmcid:PMC3266747
fatcat:qmmy5bdtcbfbngve3yrsi2foea
Identification of regular and chaotic isothermal trajectories of a shape memory oscillator using the 0–1 test
2012
Proceedings of the Institution of mechanical engineers. Proceedings part K, journal of multi-body dynamics
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The analysis is based on the computation of the control parameter K that approaches asymptotically 0 or 1 for regular and chaotic motions, respectively. ...
The presented approach is independent of the integration procedure, being based on the characteristic sampling distance between the points of the analysed time series. ...
Consequently, the regression analysis [18, 19, 20] of the linear growth of M (n, c) (Eq. 6) with increasing n is performed using the linear correlation coefficient which determines the value of the searching ...
doi:10.1177/1464419312447498
fatcat:ljnuf4vjufcnnkrjlakfus7rcq
Valid Confidence Intervals and Inference in the Presence of Weak Instruments
1998
International Economic Review
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We investigate confidence intervals and inference for the instrumental variables model with weak instruments. ...
We show that the practice of "pre-testing" by looking at the significance of the first-stage regression and then making inference based on the Wald statistic leads to extremely poor results when the instruments ...
Since an unbounded confidence set occurs when the coefficient a in ( 8 ) is less than zero, we are able to link unboundedness with goodness-of-fit statistics for the first stage regression as follows: ...
doi:10.2307/2527355
fatcat:33vmit6alfcznl5vdl5jqpox5e
Modeling Regression Quantile Process Using Monotone B-Splines
2016
Technometrics
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In this paper, we proposed a regression quantile process estimation method based on monotone B-splines. ...
The proposed method can easily ensure the validity of the regression quantile process, and offers a concise framework for variable selection and adaptive complexity control. ...
Acknowledgments: We would like to thank the editor, associate editor, and two anonymous referees for their constructive comments and suggestions that have considerably improved the paper. ...
doi:10.1080/00401706.2016.1211553
fatcat:3wmlb5yqvjf7zlcwte3ccrrvmq
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