### Table 4.1: Expected values of k The amount of interference power seen from an interferer k at direction-of-arrival of k is then:

1998

Cited by 2

### TABLE 2d: Parameter estimates of ARFIMA models for u*t

### Table 7 Estimated Reduction in Generalization Error (%)

1998

"... In PAGE 7: ...hoose the value of d from the set {.05,.10,.25,.50,75,1.00} that gave the best performance on sample size 100. The test set results are summarized in Table7 where the numbers in parentheses are the best value of d. Table 7 Estimated Reduction in Generalization Error (%)... ..."

Cited by 5

### Table 1b Model complexitya performance of AKM for n =50

"... In PAGE 15: ... At n = 50 there are 6 of 15 mixtures for which ^ fR amp;W outperforms ^ f ^ mn under this criterion, at n = 250 the ratio drops to 5=15, and for n = 1000 there are 2 of the 15 mixtures for which one would choose ^ fR amp;W over ^ f ^ mn. A discrepancy exists between the results reported in Tables 1 and 2 for R amp;W and those originally reported in Table1 of Roeder and Wasserman (1997). The results presented here for R amp;W are obtained using their code (personal communication, KR).... In PAGE 15: ... The results presented here for R amp;W are obtained using their code (personal communication, KR). The discrepancy is due to a bookkeeping error in Table1 of Roeder and Wasserman (1997) (personal communication, LW). 3.... ..."

### Table 1 Estimates and standard errors for parameters in the simulation models. Presence of IC IC=0

in Tweedie Class Log-linear Models for Longitudinal Data with Random Effects and Internal Correlation

"... In PAGE 10: ... The focus of the study is on the comparison of the consequences of the negligence and inclusion of IC. Table1 reports the numerical results of estimates and standard errors under assumptions of zero-IC (or genuine random e ects model) and of the presence of IC. Table 1 Estimates and standard errors for parameters in the simulation models.... ..."

### Table 1: Dynamic aperture estimates for the 2D model.

"... In PAGE 7: ... We computed the dynamic aperture over N = 1000 turns for di erent values of the param- eter , having set the tune to the value x = 0:28. In Table1 we show the dynamic apertures evaluated using the described methods (i.e.... In PAGE 8: ...ber of integration steps and checking the stability of the computed dynamic aperture within the error. In the last row of Table1 the average relative error of r0, rd, rnf with respect to r is given. In all the numerical simulations, the number of steps in r was 100; rd was computed over 100 iterates, and the normal form estimate rnf was evaluated using a truncation order between 3 and 8, choosing the order which minimizes the error provided by the composition of the conjugating functions and .... ..."

### Table 5: Simulated Wholesale Price Differential Due to Unexpected Refinery Outages (cents per gallon, standard errors in parentheses)

2006

"... In PAGE 20: ...he point estimates for the average magnitude of local refinery outages are 6.7, 7.3 and 7.7 cents per gallon for California, Chicago and Milwaukee respectively, although they cannot be distinguished statistically. The estimates in Table5 provide a metric by which to normalize the estimates of the effect of compatibility with federal RFG across the three states. Calculating the ratio of the effect 38Substantial variation in the magnitude of local outages exists - the model predicts that the largest outages in California, Illinois and Wisconsin increase gasoline prices by 20-30 cents per gallon.... ..."

### Table 4: Relative Performance of Blurred Segmentation and Kernel Estimators in 2-D. The values shown are estimated values of E and from modeling the ratio of RMS errors for the Blurred segmentation and kernel estimators as E ( n n0 )? , with n0 = 10000 . Approximate standard errors are given in parentheses. Case Signal E

"... In PAGE 12: ... with n0 = 10000. Table4 shows the estimates values for E and obtained from this analysis. In all cases the values of are positive indicating that the blurred segmentation tends to increase its domination over the kernel method at larger sample sizes.... ..."

### Table 1: Improvement of the estimated rotation parameters for the `planar surfaces apos; in the presence

1999

"... In PAGE 8: ... In the examples of the `planar surfaces apos; and the `teapot apos; model, the motion elds were arti cially disturbed by uniformly distributed random noise, in order to illustrate how the proposed guidelines improve the algorithm apos;s performance in the presence of noise. In this sense, Table1 depicts the improvement in the estimation of rotation parameters for the `planar surfaces apos; for increasing number... ..."

Cited by 1

### Table 11 Estimation Results for Model (40)

"... In PAGE 18: ...5208. (40) Least squares estimation results of the above specified model are given in Table11 . The indicator matrices for the residual sample cross-correlations and the residual PAM are given in Table 12 and do not show any model inadequacy.... In PAGE 18: ...he stochastic modeling of real (i.e., inflation-adjusted) investment returns is useful for pricing and designing long-term indexing insurance contracts (Wilkie 1981). Our fitted multivariate SETAR model in Table11 can be used for generating inflation-adjusted returns. As an illustration, we generate 10 years of S amp;P 500 total log returns (y3t) and inflation rates (y1t) from the fitted model.... ..."