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A Comparison of Two Averaging Techniques with an Application to Growth Empirics |
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9 |
A Comparison of Two Averaging Techniques with an Application to Growth Empirics |
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10 |
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53 |
A classical problem in linear regression or how to estimate the mean of a univariate normal distribution with known variance |
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6 |
A classical problem in linear regression or how to estimate the mean of a univariate normal distribution with known variance |
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1 |
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19 |
A note on instrumental variables and maximum likelihood estimation procedures |
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A note on instrumental variables and maximum likelihood estimation procedures |
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17 |
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77 |
A representation theorem for (trAp)1/p |
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11 |
ASYMPTOTIC NORMALITY OF THE MAXIMUM LIKELIHOOD ESTIMATOR IN THE NONLINEAR REGRESSION MODEL WITH NORMAL ERRORS |
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6 |
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18 |
Adaptation for Mitigation |
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29 |
Adaptation for Mitigation |
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39 |
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71 |
Adaptation for Mitigation |
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10 |
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1 |
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56 |
Adaptation for mitigation |
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13 |
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48 |
An experiment in applied econometrics |
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5 |
Are Economic Agents Successful Optimizers? An Analysis Through Strategy in Tennis |
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8 |
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2 |
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56 |
Are Economic Agents Successful Optimizers? An Analysis through Service Strategy in Tennis |
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112 |
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319 |
Asymptotic normality of maximum likelihood estimators obtained from normally distributed but dependent observations |
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16 |
Asyptopic Properties of Maximum Likelihood Estimators in a Nonlinear Regression Model with Unknown Parameters in the Disturbance Convariance Matrix |
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1 |
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5 |
Bayesian Integration of Large Scale SNA Data Frameworks with an Application to Guatemala |
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11 |
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43 |
Bayesian Model Averaging and Weighted Average Least Squares: Equivariance, Stability, and Numerical Issues |
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36 |
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115 |
Benzine is al eens duurder geweest |
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8 |
Burr Utility |
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5 |
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28 |
CONSISTENT MAXIMUM LIKELIHOOD ESTIMATION OF THE NONLINEAR REGRESSION MODEL WITH NORMAL ERRORS |
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4 |
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12 |
CONSISTENT MAXIMUM LIKELIHOOD ESTIMATION WITH DEPENDENT OBSERVATIONS: THE GENERAL (NON-NORMAL) CASE AND THE NORMAL CASE |
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18 |
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44 |
Climate Change, Economic Growth, and Health |
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27 |
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97 |
Climate change, economic growth, and health |
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66 |
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128 |
Comments on “Unobservable Selection and Coefficient Stability-Theory and Evidence” and “Poorly Measured Confounders are More Useful on the Left Than on the Right” |
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56 |
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161 |
Concept-Based Bayesian Model Averaging and Growth Empirics |
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7 |
Concept-Based Bayesian Model Averaging and Growth Empirics |
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7 |
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35 |
Consistency of Maximum Likelihood Estimators When Observations Are Dependent |
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Consistent maximum-likelihood estimation with dependent observations: the general (non-normal) case and the normal case |
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31 |
De kans om een tenniswedstrijd te winnen: Federer-Nadal in de finale van Wimbeldon 2007 |
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3 |
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17 |
Design of the experiment |
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10 |
EVALUATION OF MOMENT OF QUADRATIC FORMS IN NORMAL VARIABLES |
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1 |
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270 |
EVALUATION OF MOMENTS OF RATIOS OF QUADRATIC FORMS IN NORMAL VARIABLES AND RELATED STATISTICS |
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254 |
Earthquake risk embedded in property prices: Evidence from five Japanese cities |
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23 |
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73 |
Estimation of the Mean of a Univariate Normal Distribution When the Variance is not Known |
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3 |
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36 |
Estimation of the Mean of a Univariate Normal Distribution When the Variance is not Known |
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4 |
Evaluation of moments of quadratic forms and ratios of quadratic forms in normal variables: background, motivation and examples |
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5 |
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14 |
Evaluation of moments of quadratic forms in normal variables |
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10 |
Evaluation of moments of quadratic forms in normal variables |
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Evaluation of moments of ratios of quadratic forms in normal variables and related statistics |
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3 |
Evaluation of moments of ratios of quadratic forms in normal variables and related statistics |
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1 |
1 |
1 |
14 |
Expected Utility and Catastrophic Risk |
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41 |
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94 |
Expected Utility and Catastrophic Risk in a Stochastic Economy-Climate Model |
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13 |
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2 |
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71 |
Expected Utility and Catastrophic Risk in a Stochastic Economy-Climate Model |
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10 |
FORECASTING, MISSPECIFICATION AND UNIT ROOTS: THE CASE OF AR(1) VERSUS ARMA (1,1) |
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332 |
Forecast Accuracy after Pretesting with an Application to the Stock Market |
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5 |
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28 |
Forecast Accuracy after Pretesting with an Application to the Stock Market |
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1 |
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8 |
Forecasting the Winner of a Tennis Match |
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25 |
Forecasting the Winner of a Tennis Match |
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47 |
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171 |
Forecasting, misspecification and unit roots: The case of Ar(1) versus ARMA(1,1) |
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4 |
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18 |
Forecasting, misspecification and unit roots: The case of Ar(1) versus ARMA(1,1) |
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1 |
1 |
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2 |
6 |
Global Warming and Local Dimming: The Statistical Evidence |
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1 |
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17 |
Global Warming and Local Dimming: The Statistical Evidence |
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5 |
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1 |
1 |
62 |
Grade Expectations: Rationality and Overconfidence |
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89 |
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4 |
191 |
How to reduce the service dominance in tennis? Empirical results from four years at Wimbledon |
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5 |
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33 |
Inter-fuel substitution in Dutch manufacturing |
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3 |
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29 |
L-structured matrices and linear matrix equations |
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3 |
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9 |
Least squares autoregression with near-unit root |
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4 |
Local Sensitivity and Diagnostic Tests |
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7 |
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45 |
Local Sensitivity and Diagnostic Tests |
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3 |
MATRIX DIFFERENTIAL CALCULUS AND STATIC OPTIMIZATION part II- differentials: Theory |
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5 |
1 |
1 |
1 |
23 |
Macro accounts estimation using indicator ratios |
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3 |
Matrix differential calculus and static optimization Part III- differentials: Practice |
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2 |
7 |
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22 |
Matrix differential calculus with applications to simple, Hadamard, and Kronecker products |
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11 |
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2 |
45 |
Maximum Likelihood Estimation of the Multivariate Normal Mixture Model |
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84 |
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1 |
3 |
380 |
Maximum likelihood estimation of the GLS model with unknown parameters in the disturbance covariance matrix |
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0 |
3 |
1 |
1 |
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30 |
Maximum likelihood estimation of the GLS model with unknown parameters in the disturbance covariance matrix |
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0 |
0 |
3 |
0 |
1 |
1 |
21 |
Maximum likelihood estimation of the multivariate normal mixture model |
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1 |
0 |
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23 |
Multivariate error components analysis of linear and nonlinear regression models by maximum likelihood |
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1 |
2 |
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43 |
Normal's deconvolution and the independence of sample mean and variance (problem 03.4.1) |
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0 |
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5 |
Notation in Econometrics: A Proposal for a Standard |
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39 |
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2 |
177 |
Notation in Econometrics: A Proposal for a Standard |
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1 |
1 |
0 |
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4 |
ON THE FIRST-ORDER EFFICIENCY AN DASYMPTOTIC NORMALITY OF THE MAXIMUM LIKELIHOOD ESTIMATOR OBTAINED FROM DEPENDENT OBSERVATIONS |
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0 |
1 |
1 |
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8 |
ON THE FIRST-ORDER EFFICIENCY AND ASYMPOTIC NORMALITY OF THE MAXIMUM LIKELIHOOD ESTIMATOR OBTAINED FROM DEPENDENT OBSERVATIONS |
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0 |
0 |
1 |
1 |
1 |
1 |
12 |
On Theil's Errors |
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1 |
0 |
0 |
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6 |
On Theil's Errors |
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1 |
3 |
0 |
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1 |
29 |
On Theils' errors |
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1 |
0 |
0 |
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5 |
On certain moments relating to ratios of quadratic forms in normal variables: Further results |
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4 |
On differentiating eigenvalues and eigenvectors |
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1 |
2 |
33 |
1 |
1 |
5 |
84 |
On levies to reduce the nitrogen surplus: The case of Dutch pig farms |
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0 |
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1 |
1 |
1 |
22 |
On some definitions in matrix algebra |
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106 |
0 |
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1 |
262 |
On tests and significance in econometrics |
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0 |
0 |
7 |
0 |
0 |
2 |
57 |
On tests and significance in econometrics |
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0 |
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18 |
0 |
0 |
5 |
59 |
On tests and significance in econometrics |
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0 |
0 |
0 |
0 |
0 |
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3 |
On the Ambiguous Consequences of Omitting Variables |
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0 |
0 |
49 |
0 |
0 |
1 |
85 |
On the Asymptotic Normality of the Maximum Likelihood Estimator With Dependent Observations |
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0 |
0 |
4 |
0 |
0 |
0 |
13 |
On the Choice of Prior in Bayesian Model Averaging |
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0 |
0 |
0 |
1 |
1 |
2 |
5 |
On the Choice of Prior in Bayesian Model Averaging |
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0 |
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16 |
1 |
2 |
4 |
76 |
On the Harm that Pretesting Does |
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0 |
0 |
0 |
0 |
0 |
0 |
5 |
On the Harm that Pretesting Does |
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0 |
0 |
3 |
0 |
0 |
0 |
28 |
On the Independence and Identical Distribution of Points in Tennis |
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0 |
0 |
13 |
0 |
0 |
0 |
44 |
On the Independence and Identical Distribution of Points in Tennis |
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0 |
0 |
3 |
0 |
0 |
0 |
10 |
On the Unbiasedness of Iterated GLS Estimators |
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0 |
0 |
2 |
1 |
1 |
5 |
22 |
On the ambiguous consequences of omitting variables |
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0 |
0 |
16 |
0 |
0 |
1 |
74 |
On the estimation of a large sparse Bayesian system: the Snaer program |
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0 |
0 |
36 |
0 |
0 |
0 |
132 |
On the first-order efficiency and asymptotic normality of maximum likelihood estimators obtained from dependent observations |
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0 |
0 |
1 |
0 |
0 |
1 |
15 |
On the first-order efficiency and asymptotic normality of the maximum likelihood estimator obtained from dependent observations |
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0 |
0 |
2 |
0 |
0 |
2 |
11 |
On the fundamental bordered matrix of linear estimation |
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0 |
0 |
2 |
0 |
0 |
0 |
4 |
On the fundamental bordered matrix of linear estimation |
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0 |
1 |
2 |
0 |
0 |
2 |
6 |
On the maximum likelihood estimation of multivariate regression models containing serially correlated error components |
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0 |
0 |
1 |
0 |
0 |
1 |
7 |
On the maximum likelihood estimation of multivariate regression models containing serially correlated error components |
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0 |
0 |
3 |
0 |
0 |
0 |
19 |
On the sensitivity of the t-statistic |
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0 |
0 |
1 |
0 |
0 |
1 |
4 |
On the sensitivity of the usual t-and f-tests to AR(1) misspecification |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
13 |
On the sensitivity of the usual t-and f-tests to AR(1) misspecification |
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0 |
0 |
0 |
0 |
0 |
0 |
1 |
On the unbiasedness of iterated GLS estimators |
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0 |
0 |
1 |
0 |
1 |
1 |
8 |
Optimal taxation for the reduction of nitrogen surplus in Dutch dairy farms, 1975 to 1989 |
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0 |
0 |
0 |
0 |
0 |
1 |
10 |
Organization of the experiment |
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0 |
0 |
0 |
0 |
0 |
0 |
10 |
Peer Reporting and the Perception of Fairness |
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0 |
0 |
3 |
0 |
0 |
1 |
55 |
Peer Reporting and the Perception of Fairness |
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0 |
0 |
0 |
0 |
0 |
1 |
4 |
Posterior moments and quantiles for the normal location model with Laplace prior |
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0 |
0 |
13 |
0 |
0 |
1 |
63 |
Practical use of sensitivity in econometrics with an illustration to forecast combinations |
0 |
0 |
0 |
26 |
0 |
0 |
0 |
18 |
Records in Athletics through Extreme-Value Theory |
0 |
0 |
1 |
10 |
0 |
0 |
8 |
78 |
Records in Athletics through Extreme-Value Theory |
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0 |
1 |
2 |
0 |
0 |
2 |
14 |
Resource Abundance and Resource Dependence in China |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
5 |
Resource Abundance and Resource Dependence in China |
0 |
0 |
0 |
32 |
0 |
0 |
0 |
154 |
SYMMETRY, 0-1 MATRICES, AND JACOBIANS: A REVIEW |
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0 |
1 |
3 |
1 |
1 |
3 |
20 |
Sampling properties of the Bayesian posterior mean with an application to WALS estimation |
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0 |
0 |
26 |
0 |
0 |
0 |
32 |
Sampling properties of the Bayesian posterior mean with anapplication to WALS estimation |
0 |
0 |
0 |
10 |
0 |
0 |
1 |
37 |
Scrap Value Functions in Dynamic Decision Problems |
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0 |
1 |
7 |
0 |
1 |
3 |
71 |
Scrap Value Functions in Dynamic Decision Problems |
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0 |
0 |
0 |
0 |
0 |
1 |
6 |
Separability and aggregation |
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0 |
0 |
0 |
0 |
0 |
0 |
5 |
Separability and aggregation |
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0 |
0 |
2 |
0 |
0 |
1 |
12 |
Some properties of a generalized two-error components matrix (problem 01.5.1) |
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0 |
0 |
0 |
0 |
0 |
1 |
15 |
Substitution between energy and non-energy inputs in the Netherlands, 1950-1974 |
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0 |
0 |
2 |
1 |
2 |
2 |
13 |
Substitution between energy and non-energy inputs in the Netherlands, 1950-1976 |
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0 |
0 |
4 |
0 |
0 |
1 |
15 |
Substitution between energy and other inputs in the Netherlands, with contributions to related econometric problems |
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0 |
0 |
1 |
0 |
0 |
0 |
7 |
Symmetry, 0-1 matrices and Jacobians: A review |
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0 |
0 |
3 |
0 |
0 |
0 |
18 |
Testing some common hypotheses: Four years at Wimbledon |
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1 |
3 |
0 |
0 |
1 |
12 |
Testing some common tennis hypotheses: Four years at Wimbledon |
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0 |
0 |
0 |
0 |
0 |
0 |
2 |
Testing some common tennis hypotheses: Four years at Wimbledon |
0 |
0 |
0 |
14 |
0 |
1 |
1 |
112 |
Testing the Sensitivity of OLS when the Variance Maxtrix is (Partially) Unknown |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
22 |
Testing the Sensitivity of OLS when the Variance Maxtrix is (Partially) Unknown |
0 |
0 |
0 |
1 |
0 |
0 |
1 |
3 |
The ET interview: Professor J. Tinbergen |
0 |
2 |
2 |
3 |
1 |
3 |
4 |
17 |
The Forecast Combination Puzzle: A Simple Theoretical Explanation |
0 |
0 |
0 |
101 |
0 |
0 |
0 |
185 |
The Jacobian of the exponential function |
0 |
0 |
0 |
44 |
0 |
0 |
1 |
43 |
The Perception of Small Crime |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
7 |
The Perception of Small Crime |
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0 |
0 |
5 |
0 |
0 |
0 |
54 |
The asymptotic variance of the pseudo maximum likelihood estimator |
0 |
0 |
0 |
62 |
1 |
1 |
1 |
210 |
The bias of forecasts from a first-order autoregression |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
9 |
The bias of forecasts from a first-order autoregression (Revised version) |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
14 |
The central limit theorem for student's distribution (problem 03.6.1) |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
8 |
The commutation matrix: Some properties and applications |
0 |
1 |
2 |
52 |
0 |
1 |
5 |
182 |
The commutation matrix: some theorems and applications |
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0 |
0 |
5 |
1 |
2 |
9 |
34 |
The data: A brief description |
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0 |
0 |
0 |
0 |
0 |
1 |
5 |
The elimination matrix: Some lemmas and applications |
2 |
2 |
9 |
85 |
3 |
4 |
21 |
232 |
The evaluation of cumulants and moments of quadratic forms in normal variables (CUM): Technical description |
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0 |
0 |
1 |
0 |
0 |
0 |
9 |
The evaluation of moments of ratios of quadratic forms in normal variables and related statistics (QRMOM): Technical description |
0 |
0 |
0 |
2 |
0 |
0 |
0 |
7 |
The exact moments of a ratio of quadratic forms in normal variables |
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0 |
0 |
12 |
0 |
1 |
1 |
40 |
The exact multi-period mean-square forecast error for the first-order autoregressive model |
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0 |
0 |
0 |
0 |
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1 |
3 |
The exact multi-period mean-square forecast error for the first-order autoregressive model with an intercept |
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1 |
0 |
1 |
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10 |
The exact multi-period mean-square forecast error for the first-order autoregressive model with an intercept |
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0 |
0 |
0 |
1 |
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5 |
The exact multi-period meansquare forecast error for the first-order autoregressive model |
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0 |
0 |
0 |
0 |
0 |
1 |
6 |
The expectation of products of quadratic forms in normal variables: The practice Statistica Neerlandica |
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0 |
0 |
2 |
0 |
1 |
2 |
8 |
The forecast combination puzzle: a simple theoretical explanation |
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0 |
0 |
9 |
1 |
1 |
3 |
48 |
The maximum number of omitted variables, Problem 00.2.2 |
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0 |
0 |
0 |
0 |
0 |
0 |
6 |
The moments of products of quadratic forms in normal variables |
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2 |
4 |
16 |
0 |
2 |
5 |
40 |
The perception of climate sensitivity: Revealing priors from posteriors |
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0 |
0 |
8 |
0 |
0 |
2 |
16 |
The significance of testing in econometrics |
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0 |
0 |
3 |
0 |
0 |
0 |
7 |
Von Hamburg nach Berlin im sommer 1841: Emma Isler berichtet |
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0 |
0 |
0 |
0 |
0 |
1 |
11 |
WALS Prediction |
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0 |
0 |
6 |
0 |
0 |
0 |
63 |
WALS estimation and forecasting in factor-based dynamic models with an application to Armenia |
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0 |
0 |
10 |
0 |
0 |
0 |
89 |
WALS estimation and forecasting in factor-based dynamic models with an application to Armenia |
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0 |
0 |
1 |
0 |
0 |
5 |
15 |
Wat tenniscommentatoren niet weten: Een analyse van vier jaar Wimbledon |
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0 |
0 |
1 |
0 |
0 |
1 |
14 |
Weighted-Average Least Squares Estimation of Generalized Linear Models |
0 |
0 |
0 |
41 |
1 |
1 |
2 |
221 |
Weighted-average least squares estimation of generalized linear models |
0 |
0 |
1 |
19 |
1 |
1 |
2 |
70 |
Weitzman meets Nordhaus: Expected utility and catastrophic risk in a stochastic economy-climate model |
0 |
0 |
0 |
52 |
0 |
0 |
1 |
120 |
Zero-diagonality as a linear structure |
0 |
1 |
1 |
3 |
0 |
1 |
3 |
16 |
Total Working Papers |
3 |
12 |
55 |
1,907 |
33 |
73 |
255 |
7,938 |
Journal Article |
File Downloads |
Abstract Views |
Last month |
3 months |
12 months |
Total |
Last month |
3 months |
12 months |
Total |
03.4.1. Normal's Deconvolution and the Independence of Sample Mean and Variance |
0 |
0 |
0 |
5 |
0 |
0 |
0 |
43 |
03.6.1 The Central Limit Theorem for Student's Distribution—Solution |
1 |
1 |
1 |
19 |
1 |
1 |
1 |
76 |
03.6.1. The Central Limit Theorem for Student's Distribution |
0 |
0 |
0 |
6 |
0 |
0 |
0 |
60 |
A Note on Instrumental Variables and Maximum Likelihood Estimation Procedures |
0 |
0 |
0 |
3 |
0 |
0 |
1 |
18 |
A comparison of two model averaging techniques with an application to growth empirics |
0 |
0 |
4 |
318 |
0 |
0 |
9 |
815 |
Adaptation for Mitigation |
0 |
0 |
0 |
11 |
1 |
3 |
7 |
55 |
Are Points in Tennis Independent and Identically Distributed? Evidence From a Dynamic Binary Panel Data Model |
0 |
0 |
4 |
182 |
1 |
1 |
7 |
429 |
Asymptotic Normmality of Maximum Likelihood Estimators Obtained from Normally Distributed but Dependent Observations |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
12 |
BALANCED VARIABLE ADDITION IN LINEAR MODELS |
0 |
1 |
4 |
14 |
1 |
2 |
11 |
53 |
Bayesian model averaging and weighted-average least squares: Equivariance, stability, and numerical issues |
0 |
2 |
7 |
206 |
1 |
4 |
11 |
730 |
Comments on “Unobservable Selection and Coefficient Stability: Theory and Evidence” and “Poorly Measured Confounders are More Useful on the Left Than on the Right” |
0 |
0 |
0 |
9 |
0 |
0 |
1 |
39 |
Concept-Based Bayesian Model Averaging and Growth Empirics |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
44 |
Consistent maximum-likelihood estimation with dependent observations: The general (non-normal) case and the normal case |
0 |
0 |
0 |
143 |
1 |
2 |
3 |
351 |
Design of the Experiment |
0 |
0 |
0 |
62 |
0 |
0 |
0 |
325 |
Editors' introduction: The significance of testing in econometrics |
0 |
0 |
0 |
22 |
0 |
1 |
1 |
96 |
Estimation of Regression Coefficients of Interest When Other Regression Coefficients Are of No Interest |
0 |
0 |
0 |
1 |
0 |
0 |
1 |
399 |
Estimation of Variance Components and Applications |
1 |
1 |
2 |
6 |
1 |
4 |
8 |
26 |
Estimation of the mean of a univariate normal distribution with known variance |
0 |
0 |
0 |
122 |
0 |
0 |
2 |
1,109 |
Expected utility and catastrophic consumption risk |
0 |
0 |
1 |
10 |
0 |
1 |
3 |
55 |
Expected utility and catastrophic risk in a stochastic economy–climate model |
0 |
0 |
0 |
10 |
0 |
1 |
2 |
98 |
Forecast accuracy after pretesting with an application to the stock market |
0 |
0 |
0 |
47 |
0 |
0 |
0 |
239 |
Forecasting the winner of a tennis match |
0 |
0 |
0 |
123 |
0 |
0 |
3 |
346 |
Global Warming and Local Dimming: The Statistical Evidence |
0 |
0 |
0 |
13 |
0 |
0 |
0 |
90 |
HANDBOOK OF MATRICES |
0 |
0 |
0 |
58 |
0 |
0 |
1 |
211 |
Interpretation and use of sensitivity in econometrics, illustrated with forecast combinations |
0 |
0 |
0 |
5 |
1 |
1 |
2 |
34 |
Local sensitivity and diagnostic tests |
0 |
0 |
0 |
49 |
0 |
2 |
3 |
366 |
Maximum Likelihood Estimation of the Multivariate Normal Mixture Model |
0 |
0 |
0 |
9 |
0 |
1 |
1 |
63 |
Maximum likelihood estimation of the GLS model with unknown parameters in the disturbance covariance matrix |
0 |
0 |
0 |
219 |
0 |
1 |
1 |
1,064 |
Multivariate error components analysis of linear and nonlinear regression models by maximum likelihood |
0 |
0 |
1 |
108 |
0 |
0 |
3 |
300 |
NATIONAL ACCOUNTS ESTIMATION USING INDICATOR RATIOS |
0 |
0 |
0 |
2 |
0 |
0 |
0 |
8 |
NOTES AND PROBLEMS A GENERAL BOUND FOR THE LIMITING DISTRIBUTION OF BREITUNG'S STATISTIC |
0 |
0 |
0 |
14 |
0 |
0 |
0 |
47 |
Natural Resources, Institutional Quality, and Economic Growth in China |
0 |
1 |
5 |
51 |
1 |
3 |
12 |
177 |
Notation in econometrics: a proposal for a standard |
0 |
0 |
0 |
309 |
0 |
0 |
5 |
1,445 |
ON THE FIRST–ORDER EFFICIENCY AND ASYMPTOTIC NORMALITY OF MAXIMUM LIKELIHOOD ESTIMATORS OBTAINED FROM DEPENDENT OBSERVATIONS |
0 |
0 |
0 |
1 |
1 |
1 |
2 |
15 |
On Differentiating Eigenvalues and Eigenvectors |
1 |
2 |
8 |
58 |
2 |
3 |
13 |
157 |
On Theil's errors |
0 |
0 |
0 |
48 |
0 |
0 |
0 |
249 |
On Using the t -Ratio as a Diagnostic |
0 |
0 |
1 |
9 |
0 |
0 |
1 |
22 |
On levies to reduce the nitrogen surplus: The case of Dutch pig farms |
0 |
0 |
0 |
3 |
0 |
0 |
0 |
51 |
On tests and significance in econometrics |
0 |
0 |
2 |
142 |
1 |
1 |
10 |
597 |
On the Maximum Likelihood Estimation of Multivariate Regression Models Containing Serially Correlated Error Components |
0 |
0 |
0 |
144 |
0 |
0 |
1 |
468 |
On the concept of matrix derivative |
0 |
1 |
2 |
22 |
1 |
3 |
5 |
127 |
On the estimation of a large sparse Bayesian system: The Snaer program |
0 |
0 |
0 |
3 |
0 |
0 |
1 |
35 |
On the harm that ignoring pretesting can cause |
0 |
0 |
1 |
48 |
0 |
0 |
2 |
150 |
On the sensitivity of the usual t- and F-tests to covariance misspecification |
0 |
0 |
0 |
17 |
0 |
2 |
2 |
161 |
Organization of the Experiment |
0 |
0 |
0 |
8 |
1 |
1 |
2 |
175 |
Pareto utility |
0 |
0 |
1 |
17 |
0 |
0 |
1 |
95 |
Peer Reporting and the Perception of Fairness |
0 |
0 |
0 |
5 |
0 |
0 |
1 |
68 |
Records in Athletics Through Extreme-Value Theory |
0 |
0 |
0 |
48 |
0 |
1 |
6 |
142 |
Rejoinder |
0 |
0 |
0 |
3 |
0 |
0 |
0 |
53 |
SPECIFICATION OF VARIANCE MATRICES FOR PANEL DATA MODELS |
0 |
0 |
0 |
39 |
0 |
0 |
0 |
96 |
Some equivalences in linear estimation (in Russian) |
0 |
0 |
0 |
17 |
0 |
1 |
1 |
95 |
Substitution between Energy and Non-Energy Inputs in the Netherlands, 1950-1976 |
0 |
0 |
0 |
35 |
0 |
0 |
0 |
115 |
Symmetry, 0-1 Matrices and Jacobians: A Review |
0 |
0 |
2 |
19 |
1 |
1 |
5 |
62 |
THE ASYMPTOTIC VARIANCE OF THE PSEUDO MAXIMUM LIKELIHOOD ESTIMATOR |
0 |
0 |
0 |
6 |
0 |
0 |
0 |
37 |
The Bias of Forecasts from a First-Order Autoregression |
0 |
0 |
0 |
3 |
1 |
1 |
1 |
16 |
The Data: A Brief Description |
0 |
0 |
0 |
28 |
0 |
0 |
0 |
238 |
The Exact Moments of a Ratio of Quadratic Forms in Normal Variables |
0 |
1 |
2 |
26 |
0 |
2 |
6 |
81 |
The Third Special Issue on Computational Econometrics |
0 |
0 |
0 |
46 |
1 |
1 |
1 |
138 |
The effect of health benefits on climate change mitigation policies |
0 |
0 |
0 |
9 |
0 |
1 |
2 |
38 |
The efficiency of top agents: An analysis through service strategy in tennis |
0 |
0 |
0 |
39 |
0 |
0 |
6 |
229 |
The exact multi-period mean-square forecast error for the first-order autoregressive model |
0 |
0 |
0 |
23 |
0 |
0 |
1 |
107 |
The exact multi-period mean-square forecast error for the first-order autoregressive model with an intercept |
0 |
0 |
0 |
10 |
0 |
1 |
1 |
62 |
The expectation of products of quadratic forms in normal variables: the practice |
0 |
0 |
1 |
1 |
0 |
1 |
3 |
5 |
The final set in a tennis match: Four years at Wimbledon |
0 |
0 |
1 |
197 |
1 |
1 |
3 |
824 |
The forecast combination puzzle: A simple theoretical explanation |
0 |
0 |
2 |
17 |
0 |
0 |
4 |
138 |
The moments of products of quadratic forms in normal variables* |
0 |
0 |
0 |
3 |
0 |
1 |
2 |
10 |
The perception of small crime |
0 |
0 |
0 |
17 |
0 |
0 |
0 |
119 |
The price of Moscow apartments |
0 |
1 |
5 |
188 |
1 |
4 |
25 |
511 |
The sensitivity of OLS when the variance matrix is (partially) unknown |
0 |
0 |
0 |
24 |
0 |
0 |
1 |
191 |
Tolerance of Cheating: An Analysis Across Countries |
2 |
4 |
5 |
113 |
7 |
16 |
23 |
434 |
USING MACRO DATA TO OBTAIN BETTER MICRO FORECASTS |
0 |
0 |
0 |
24 |
0 |
1 |
2 |
81 |
WALS Estimation and Forecasting in Factor-based Dynamic Models with an Application to Armenia |
0 |
0 |
0 |
15 |
2 |
2 |
2 |
199 |
WEIGHTED-AVERAGE LEAST SQUARES (WALS): A SURVEY |
0 |
0 |
0 |
10 |
0 |
0 |
0 |
67 |
Weighted average least squares estimation with nonspherical disturbances and an application to the Hong Kong housing market |
0 |
0 |
0 |
29 |
0 |
1 |
1 |
158 |
Weighted-Average Least Squares Prediction |
0 |
0 |
0 |
1 |
0 |
0 |
1 |
36 |
Weighted-average least squares estimation of generalized linear models |
0 |
0 |
0 |
18 |
1 |
1 |
8 |
88 |
Total Journal Articles |
5 |
15 |
62 |
3,691 |
30 |
76 |
245 |
15,963 |