Robustness or Efficiency, A Test to Solve the Dilemma [PDF]
When dealing with the presence of outliers in a dataset, the problem of choosing between the classical ordinary least squares and robust regression methods is sometimes addressed inadequately.
Catherine Dehon +2 more
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The Effect of Microaggregation Procedures on the Estimation of Linear Models: A Simulation Study [PDF]
, 2005 Microaggregation is a set of procedures that distort empirical data in order to guarantee the factual anonymity of the data. At the same time the information content of data sets should not be reduced too much and should still be useful for scientific ...
Schmid, Matthias, Schneeweiß, Hans
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MELE: MAXIMUM ENTROPY LEUVEN ESTIMATORS [PDF]
Multicollinearity hampers empirical econometrics. The remedies proposed to date suffer from pitfalls of their own. The ridge estimator is not generally accepted as a vital alternative to the ordinary least-squares (OLS) estimator because it depends upon ...
Paris, Quirino
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Inference on Time-Invariant Variables using Panel Data: A Pre-Test Estimator with an Application to the Returns to Schooling [PDF]
, 2010 This paper proposes a new pre-test estimator of panel data models including time invariant variables based upon the Mundlak-Krishnakumar estimator and an "unrestricted” Hausman-Taylor estimator. The paper evaluates the biases of currently used restricted
Chatelain, Jean-Bernard, Ralf, Kirsten
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Random design analysis of ridge regression
, 2014 This work gives a simultaneous analysis of both the ordinary least squares estimator and the ridge regression estimator in the random design setting under mild assumptions on the covariate/response distributions.
Hsu, Daniel +2 more
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Statistical Modeling and Estimation of Censored Pathloss Data [PDF]
, 2015 Pathloss is typically modeled using a log-distance power law with a large-scale fading term that is log-normal. However, the received signal is affected by the dynamic range and noise floor of the measurement system used to sound the channel, which can ...
Abbas, Taimoor +3 more
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On the Liu and almost unbiased Liu estimators in the presence of multicollinearity with heteroscedastic or correlated errors [PDF]
Surveys in Mathematics and its Applications, 2009 This paper introduces a new biased estimator, namely, almost unbiased Liu estimator (AULE) of β for the multiple linear regression model with heteroscedastics and/or correlated errors and suffers from the problem of multicollinearity.
Mustafa I. Alheety, B. M. Golam Kibria
doaj
Nearly Optimal Sample Size in Hypothesis Testing for High-Dimensional Regression
, 2013 We consider the problem of fitting the parameters of a high-dimensional linear regression model. In the regime where the number of parameters $p$ is comparable to or exceeds the sample size $n$, a successful approach uses an $\ell_1$-penalized least ...
Javanmard, Adel, Montanari, Andrea
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KINERJA JACKKNIFE RIDGE REGRESSION DALAM MENGATASI MULTIKOLINEARITAS
E-Jurnal Matematika, 2014 Ordinary least square is a parameter estimations for minimizing residual sum of squares. If the multicollinearity was found in the data, unbias estimator with minimum variance could not be reached.
HANY DEVITA +2 more
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Cancerphobia: Electromagnetic Fields and Their Impact on Residential Loan Values [PDF]
This article provides a matrix representation of the adjustment grid estimator. From this representation, one can invoke the Gauss-Mrkov theorem to examine the efficiency of ordinary least squares (OLS) and the grid estimator that uses OLS estimates of ...
Donald R. Epley, James A. Bryant
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