Emerging Needs and Tailored Products 3 pdf

... MRS Model (Structure: 4 Lags, 3 Neurons) Diagnostic Linear Model (Network Model) Estimate R 2 .35 ( .38 ) HQIF 32 91 (32 68) L-B ∗ .91 M-L ∗ .0009 E-N ∗ .0176 J-B ∗ .36 L-W-G 13 B-D-S∗ .0002 ∗ marginal ... model, they do 132 5. Estimating and Forecasting with Artificial Data 0 50 100 150 200 250 30 0 35 0 400 450 500 −6 −4 −2 0 2 4 6 8 0 50 100 150 200 250 30 0 35 0 400 450 500 0...

Ngày tải lên: 21/06/2014, 09:20

... of falling in category 1, 2, or 3 come from the cumulative probabilities: p 1,i = P 1,i  3 j=1 P j,i (2.89) p 2,i = P 2,i  3 j=1 P j,i (2.90) p 3, i = P 3  3 j=1 P j,i (2.91) Neural network ... between long- and short-term rates for government bonds, the expected and unexpected inflation rates, industrial production growth, and the yield between corporate high and low-gra...

Ngày tải lên: 21/06/2014, 07:20

... properties, 82 3. Estimation of a Network with Evolutionary Computation 0 100 200 30 0 400 500 600 700 800 900 1000 −4 3 −2 −1 0 1 2 3 0 100 200 30 0 400 500 600 700 800 900 1000 0 5 10 15 20 25 x1=randn(1000,1) y1=sin(x1) 2 ... p. 31 5]. As Table 3. 2 shows, we again start with a candidate solution vector, Ω 0 , and the associated error criterion, Ψ 0 . A shock to the solution ve...

Ngày tải lên: 21/06/2014, 07:20

... ols1.m, wnnest1.m, and bds.m, available on the webpage of the author. % Create random regressors, constant term, % and dependent variable for i = 1:1000, randn(’state’,i); xxx = randn(1000,1); x1 ... boostrapping method originally due to Efron (1979, 19 83) and Efron and Tibshirani (19 93) . This bootstrapping method is different from the . 632 bootstrap method for in-sample bias. In t...

Ngày tải lên: 21/06/2014, 07:20

... MRS Model (Structure: 4 Lags, 3 Neurons) Diagnostic Linear Model (Network Model) Estimate R 2 .35 ( .38 ) HQIF 32 91 (32 68) L-B ∗ .91 M-L ∗ .0009 E-N ∗ .0176 J-B ∗ .36 L-W-G 13 B-D-S∗ .0002 ∗ marginal ... Model 133 TABLE 5.9. In-Sample Diagnostics: VRS Model (Structure: 4 Lags, 3 Neurons) Diagnostic Linear Model (Network Model) Estimate R 2 .422 (. 438 ) HQIF 34 84 (34 88) L-B ∗ ....

Ngày tải lên: 21/06/2014, 07:20

... Costs Mean 0 .30 0 −0.060 0.027 0.086 0. 234 0.016 0.082 1985 0.294 −0.056 0.024 0.050 0.226 −0.015 0.072 1996 0 .30 0 −0.060 0.027 0.091 0. 235 0.020 0.084 2002 0 .30 9 −0.067 0. 032 0. 130 0.244 0.0 53 0.0 93 Statistical ... Index Costs Mean 0 .31 2 −0. 037 0.0 93 0.168 0 .30 6 0.055 0.141 1985 0.295 −0.018 0.071 0.182 0.292 0.051 0.1 23 1996 0 .32 0 −0.046 0.1 03 0.161 0 .31 2 0.056 0...

Ngày tải lên: 21/06/2014, 07:20

... 23. 500 22 .30 0 21.000 20.000 Std. Dev. 12.906 10.1 83 8.1 23 6.719 5. 238 4 .30 3 Coeff. Var 0.4516 0 .38 88 0 .33 448 0.2927 0.246 0.216 Skewness 0.487 0.590 0.582 0. 536 0.404 0.584 Kurtosis 2.064 2. 235 ... 0.591 0.500 0.428 0 .37 2 0 .30 0 0. 239 Skewness 1.122 1.214 1.2 23 1.191 1.092 0.952 Kurtosis 2.867 3. 114 3. 186 3. 156 3. 0 23 2. 831 Max 66.000 59.000 50.000 44 .30 0 3...

Ngày tải lên: 21/06/2014, 07:20

... regression techniques. [Dayhoff and DeLeo (2001), p. 1624]. 32 2. What Are Neural Networks? {y} can be decomposed into linear and nonlinear components, and then we would expect all three sets of coefficients, {β}, {ω}, and ... from the input vector and the center of that unit, whereas the MLP or feedforward network computes the inner products of the inputs and the weights for that...

Ngày tải lên: 21/06/2014, 09:20

... p. 31 5]. As Table 3. 2 shows, we again start with a candidate solution vector, Ω 0 , and the associated error criterion, Ψ 0 . A shock to the solution vector is then randomly generated, Ω 1 , and ... the 82 3. Estimation of a Network with Evolutionary Computation 0 100 200 30 0 400 500 600 700 800 900 1000 −4 3 −2 −1 0 1 2 3 0 100 200 30 0 400 500 600 700 800 900 1000 0 5 10 15...

Ngày tải lên: 21/06/2014, 09:20