### Table 1. The mean and maximum absolute errors of various bivariate interpolation methods for a test function.

"... In PAGE 12: ... 5, Renka and Cline, 1984). The accuracy of the interpolation was tested at 33 33 regular grid points and compared with results obtained from other methods ( Table1 ). From these results, at least for this type of surface, CRS has the greatest accuracy.... In PAGE 12: ... Interpolation with tension The in uence of tension on an interpolated surface is demonstrated on a bivariate function with fault, originally presented by Nielson and Franke (1984). The function was sampled over 33 scattered data points within the unit square (data were taken from Table1 , Nielson and Franke, 1984). The result of applying the thin plate spline to these data (Fig.... ..."

### Table 1. The mean and maximum absolute errors of various bivariate interpolation methods for a test function.

"... In PAGE 12: ... 5, Renka and Cline, 1984). The accuracy of the interpolation was tested at 33 33 regular grid points and compared with results obtained from other methods ( Table1 ). From these results, at least for this type of surface, CRS has the greatest accuracy.... In PAGE 12: ... Interpolation with tension The in uence of tension on an interpolated surface is demonstrated on a bivariate function with fault, originally presented by Nielson and Franke (1984). The function was sampled over 33 scattered data points within the unit square (data were taken from Table1 , Nielson and Franke, 1984). The result of applying the thin plate spline to these data (Fig.... ..."

### Table 3.2 Average Daily Temperature and Temperature Gradient for all Levels at Different Temperature Trends (N.B. negative number indicates temperature decreases with depth)

1997

### Table 4. Comparison between Harvest TOPEX altimeter bias estimates using 1-day JGM-2 and 10-day reduced dynamic JPL orbits. These bias estimates are based on fast-rate data and were obtained by using a 5th-order polynomial as interpolator

"... In PAGE 12: ... An additional comparison was performed between bias estimates based on the 1-day JGM- 2 orbits and the 10-day JPL GPS reduced dynamics orbits. Table4 shows the bias estimate comparison using 6 cycles (cycles 10,15,17,18,19, and 21). Again, Table 4 shows that a positive o set exists between the estimates using the two di erent types of orbits.... In PAGE 12: ... Table 4 shows the bias estimate comparison using 6 cycles (cycles 10,15,17,18,19, and 21). Again, Table4 shows that a positive o set exists between the estimates using the two di erent types of orbits. The o set value compares very well with the orbit di erences between the JGM-2 orbits and the orbits computed using the TOPEX tuned gravity eld model (Table 2).... ..."

### Table 7-9. Final Sampling Design. (2 pages)

1996

"... In PAGE 48: ...1.1 Screening Method Alternatives Table7 -1 identifies all of the screening technologies that were considered to resolve each decision statement and the optional methods of implementing each technology. The table also summarizes the limitations associated with each screening technology and/or method of implementation and provides an estimated cost for implementation.... In PAGE 48: ... The table also summarizes the limitations associated with each screening technology and/or method of implementation and provides an estimated cost for implementation. Table7 -1. Summary of Screening Alternatives.... In PAGE 48: ...1.2 Sampling Method Alternatives Table7 -2 identifies the various types of media that need to be sampled to resolve each decision statement and alternative methods for collecting these samples. The table presents alternative... In PAGE 49: ... An estimated cost for the implementation of each sampling design has also been provided for comparison purposes. Table7 -2. Summary of Sampling Method Alternatives.... In PAGE 49: ...1.3 Implementation Design Table7 -3 presents the selected screening technology(s) and sampling method(s) for resolving each decision statement and a summary of the proposed implementation design. The table also provides the rationale for selected methods and design.... In PAGE 49: ... The table also provides the rationale for selected methods and design. Table7 -3. Selected Judgmental Design.... In PAGE 50: ...2.1 Data Collection Design Alternatives Table7 -4 identifies the statistical design alternatives (e.g.... In PAGE 50: ...able 7-4 identifies the statistical design alternatives (e.g., simple random, stratified random, and systematic) that were evaluated for each decision statement, as well as the selected design and the rationale for the selection. Table7 -4. Selected Statistical Design.... In PAGE 50: ...2.2 Mathematical Expressions for Solving Design Problems Table7 -5 identifies the statistical hypothesis test (e.g.... In PAGE 51: ...Rev. 0 7-4 Table7 -5. Statistical Methods for Testing the Null Hypothesis.... In PAGE 52: ...2.3 Select the Optimal Sample Size that Satisfies the Data Quality Objectives Table7 -6 presents the total number of samples required to be collected for each decision statement with varying error tolerances and varying widths of the gray region. The total number of samples was calculated using the statistical method identified in Table 7-4.... In PAGE 52: ....2.3 Select the Optimal Sample Size that Satisfies the Data Quality Objectives Table 7-6 presents the total number of samples required to be collected for each decision statement with varying error tolerances and varying widths of the gray region. The total number of samples was calculated using the statistical method identified in Table7 -4. As would be expected, the higher the error tolerances and wider the gray region, the smaller the number of samples that are required.... In PAGE 52: ...7 [EPA 1989]). As shown in Table7 -4, the fill material in 105-F FSB is considered analogous to waste site overburden, thus, the 100 Area SAP (DOE-RL 1998a) sampling strategy will be used. Table 7-6.... In PAGE 52: ...-Test (formula 6.7 [EPA 1989]). As shown in Table 7-4, the fill material in 105-F FSB is considered analogous to waste site overburden, thus, the 100 Area SAP (DOE-RL 1998a) sampling strategy will be used. Table7 -6. Sample Size Based on Varying Error Tolerances and LBGR.... In PAGE 53: ...2.4 Sampling Cost For varying error tolerances, and varying widths of the gray region, Table7 -7 presents the total cost for sampling and analyzing the number of samples identified in Table 7-6. As would be expected, the higher the error tolerances, the wider the gray region, the lower the sampling and analysis costs.... In PAGE 53: ...2.4 Sampling Cost For varying error tolerances, and varying widths of the gray region, Table 7-7 presents the total cost for sampling and analyzing the number of samples identified in Table7 -6. As would be expected, the higher the error tolerances, the wider the gray region, the lower the sampling and analysis costs.... In PAGE 53: ... Consult the appendices in the Remedial Design Report/Remedial Action Workplan for the 100 Area (DOE-RL 1998b) for the results of the trade-off analysis. Table7 -7. Sampling Cost Based on Varying Error Tolerances and LBGR.... In PAGE 53: ... It is important to consider trade-offs so contingency plans can be developed and the added value of selecting one set of considerations over another can be quantified. Table7 -8 identifies the sampling design that provides a balance between the known operational limitations and the ability to meet the DQOs. Once the sample design has been defined, the project may conduct a trade-off analysis to determine if the reused potential... In PAGE 54: ...Rev. 0 7-7 Table7 -8. Most Resource-Effective Data Collection Design.... In PAGE 54: ... If required, one or more outputs to DQO Steps 1 through 6 were modified to tailor the design to most efficiently meet all of the DQO constraints. For each decision statement, Table7 -9 presents a summary of the final statistical sampling design, the total number of samples to be collected. Sampling will be performed as described in Table 7-8.... In PAGE 54: ... Sampling will be performed as described in Table 7-8. Table7 -9. Final Sampling Design.... ..."

Cited by 2

### Table 1. Parameter settings for MEBAA interpolation algorithm.

2004

"... In PAGE 14: ... Options to find a specified number of points in each quadrant and to use all data points are not used. Settings used in the MEBAA interpolation are shown in Table1 , below. A minimum of six scatter data points is used to determine the elevation for each interpolant.... In PAGE 15: ... region, whose size is described below in Table1 , is searched in succession. If at least six scattered data points are located inside a bounding region, the search stops and all located ... ..."

### Table 5 Univariate Bivariate

2000

"... In PAGE 25: ...eriods (i.e., a total of kt dummies). In the one-step method, there are only k time-invariant Federal Reserve district dummies, and macro effects are modelled much more parsimoniously as a linear function of changes in monetary policy and GDP.33 Table5 presents an overview of the estimates of N generated by the one-step approach. As can be seen, the point estimates are generally quite close to those in Table 3.... In PAGE 28: ... If we base our calculation on the bivariate small-bank/big-bank coefficient differential of -.1327 in Panel A of Table5 , we get a 5.3% gap in the level of C amp;I loans across the liquid and illiquid small banks one year after the rise in the funds rate.... ..."

Cited by 13

### Table 4 Bivariate Results

"... In PAGE 14: ... Cross Section Regressions on Institutional Variables The i nstitutional variables show vary little variation across time and therefore are primarily identifying cross-country differences in the likelihood of banking distress and crisis. Recognizing this data limitation, Table4 reports probit regressions using cross-section (across countries) data where the dependent variable is banking distress (crisis). In these regressions the dependent variable takes on a value of unity if the country in question experienced an episode of banking distress (crisis) at any time during the sample period.... In PAGE 14: ... The right-hand-side variables are the institutional variables either individually (in the upper first and second panels) or jointly (in third panel). The first (second) panel of Table4 reports the results from the bivariate regr essions with banking distress (crisis) as the dependent variable regressed on each of the new institutional variables investigated in this study. (Constant terms are included in all of the regressions but are not reported for brevity).... ..."

### Table 1 Complexity results on conversions between Newton and monomial bases, monomial evaluation and interpolation, Newton evaluation and interpolation.

"... In PAGE 3: ... We also discuss applications to computations with differential operators and polynomial matrix multiplication. Table1 summarizes the best results known to us on the three questions men- tioned above; we now review its columns in turn and detail our contributions. In what follows, all results of type O(M(n) log(n)) are valid when n is a power of 2.... In PAGE 16: ... Newton interpolation and evaluation. We first recall the algorithm of (?, Section 3): this gives the last two entries of the second column, in Table1 . For further discussion, we detail the proof.... In PAGE 18: ... Conversion between monomial and Newton bases. To fill the second column of Table1 , our next step is to consider the base change algorithms, which occupy the first and second rows. To perform these conversions, we use the same algorithms as in the case of arbitrary sample points; the complexity results are thus those given in the previous section.... ..."