### Table 1: Individual and aggregate throughput for 2 contending TCP tra c streams.

"... In PAGE 8: ... 3.4 Numerical Results Table1 through Table 3 summarize the results of a set of experiments testing the performance of Credit-Based Congestion Control. All individual throughput values presented in the tables are averages taken over a repetition of ten experi- ments.... In PAGE 8: ... All individual throughput values presented in the tables are averages taken over a repetition of ten experi- ments. From Table1 , we can observe that when two courteous tra c streams com- pete for the same link, the aggregate throughput without congestion control is almost 15% lower than that with congestion control. The reason for this is that while TCP apos;s backo mechanism prevents severe throughput degradation, it cannot prevent cell losses from happening at the switch.... ..."

### Table 4: Standard Deviation of Changes over Time in Aggregate Governance Indicators

2003

"... In PAGE 17: ... The first thing to note is that changes in the estimates of governance tend to be small relative to the levels of governance. This can be seen from Table4 which shows, for each of the six indicators, the standard deviation (across countries) of changes in governance over the periods 2002-2000, 2000-1998, 1998- 1996, and 2002-1996. Recall that the standard deviation of the level of governance is equal to one by construction.... ..."

Cited by 16

### Table 1. Summary of the main algorithms presented in this chapter for distinct-values estimation over a data stream of values

"... In PAGE 3: ... Summary of the main algorithms presented in this chapter for distinct-values estimation over a data stream of values distributed streams, and sensor networks. Table1 summarizes the main algo- rithms presented in this chapter. 2 Preliminary Approaches and Difficulties In this section, we consider several previously studied approaches to distinct- values estimation and the difficulties with these approaches.... ..."

### Table 3. Estimates of the population mean percentile at the subgroup level of aggregation

1997

"... In PAGE 16: ... Table3 seeks to pin down more precisely the percentile corresponding to the population mean (the population mean percentile). As discussed earlier, in the context of calculating moments of the distribution, approximations can be based on averaging of quarterly sample mean percentiles, or averaging of figures for normalised data pooled over longer periods such as calendar years or multi- year periods.... In PAGE 16: ...ear periods. Calculations based on each method are reported in table 3. Also reported in the table are median values of the sample mean percentiles, since the averages of the sample mean percentiles at the quarterly or pooled annual level are likely, in some cases, to have been significantly distorted by outliers in particular quarters. Table3 shows a surprising stability in the mean percentile over time. Once the standard errors (of 1-3 percentage points) are taken into account, it can be said that there has been no significant shift in the mean percentile over any sustained period the past 48 years.... ..."

Cited by 2

### Table 5: Update action propagation

1994

"... In PAGE 11: ... Observe that aggregate functions require, in addition to the incoming action, the entire relational expression E to which the aggregate function is applied.The formulas given in Table5 don apos;t take into account the internal structure of selection predi- cates and update expressions. In the case of simple predicates (comparisons between an attribute and a constant3) and simple arithmetic update expressions (addition or subtraction of constants from an attribute), in many cases it is possible to eliminate some of the propagated actions.... In PAGE 15: ...here name is an abbreviation for ACCOUNT.name = CUSTOMER.name and SF-cust is an abbreviation for city=0SF0CUSTOMER. Using Table5 , the propagation of Eupd through the selection operation in C yields insert and update actions (the delete action is eliminated, see Table 7). We have: E0 ins = new(( balance lt;500^rate0 gt;0Eupd) .... In PAGE 16: ... As an example, let op be a selection p performed over an arbitrary subtree S and consider an update action Ein upd associated with S and performed on an attribute in p. Applying our propagation rules from the second line of Table5 , we obtain a triple hEout ins; Eout del ; Eout updi, corresponding to tuples added to, deleted from, and updated in the result of Q = pS. It can be seen that Eout ins = new(( p0Ein upd) .... ..."

Cited by 49

### Table 2 Aggregate and disaggregate information, Relative forecast accuracy: Average RMSFE ratios over AR(p) of year-on-year inflation in percentage points . horizon 1 6 12

2005

"... In PAGE 21: ... The main criterion for the comparison of the forecasts employed in this study, as in a large part of the literature on forecasting, is the root mean square forecast error (RMSFE). Table2 and 5 present the comparison of the relative forecast accuracy measured in terms of 13Alternatively, the methods suggested by Forni et al. (2000) and Forni, Hallin, Lippi amp; Reichlin (2001) might be applied.... In PAGE 22: ...3.2 Aggregate and disaggregate information First we compare methods only based on aggregate information as opposed to forecast methods for the aggregate including disaggregate variables in addition (see Table2 , column for direct forecast for each forecast horizon). Within the framework of the general theory of prediction we have shown that including disaggregate variables in the aggregate model does improve predictability of a variable (see section 2).... In PAGE 28: ... In- cluding the respective component(s) in the forecast model might then lower forecast accuracy by increasing estimation uncertainty. This might help explaining that selection pays according to the results in Table2 where the VARagg,sub Gets outperforms all other models one month ahead. Further- more, correlation among disaggregate components included in the models decline, i.... ..."

### Table 3: Individual and aggregate throughput for contending TCP tra c streams, UDP streams, and TCP versus UDP streams, with and without congestion control. All values measured in Mb/s. See Figure 6 for topology.

"... In PAGE 10: ... put occurs without congestion control; although TCP apos;s backo mechanism prevents severe through- put degradation, it cannot prevent cell losses from occuring at the switch. Furthermore, congestion control is needed in order to guarantee fairness, as shown in the last two columns of Table3 ; with- out it, UDP tra c (B to A) dominates, taking over most of the available capacity. 5.... ..."

### Table 1: Cyclicalityofthe Aggregate Price Markup

1997

"... In PAGE 13: ... Over 1960:1 to 1996:4, the markup has a correlation with unemploymentofn000:16 and with the output gap n28den0cned as the deviation of output from trend with the trend estimated on an NBER peak-to-peak basisn29 of 0:36. 9 Table1 reports some simple regression results for the aggregate price markup, using the sample 1962:1 to 1996:4: t-statistics are in parentheses. The regression in the n0crst column shows that there is a high degree of autocorrelation in the price markup over unit labor costs with a fourth-order polynomial distributed lag estimated for 8 lag coen0ecients revealing an R 2 of 0.... In PAGE 14: ...ith the output gap of -0.29 and with the unemployment rate of 0.03. The regression in the n0cfth column of Table1 conn0crms a weak countercyclical pattern with signs on the contemporaneous and lagged output gap which are the opposite to that for the unad- justed markup, although smaller in magnitude and adding considerably less explanatory... ..."

Cited by 1

### Table 1: Cyclicality of the Aggregate Price Markup

"... In PAGE 13: ... Over 1960:1 to 1996:4, the markup has a correlation with unemployment of ?0:16 and with the output gap (de ned as the deviation of output from trend with the trend estimated on an NBER peak-to-peak basis) of 0:36.9 Table1 reports some simple regression results for the aggregate price markup, using the sample 1962:1 to 1996:4: t-statistics are in parentheses. The regression in the rst column shows that there is a high degree of autocorrelation in the price markup over unit labor costs with a fourth-order polynomial distributed lag estimated for 8 lag coe cients revealing an R2 of 0.... In PAGE 14: ...ith the output gap of -0.29 and with the unemployment rate of 0.03. The regression in the fth column of Table1 con rms a weak countercyclical pattern with signs on the contemporaneous and lagged output gap which are the opposite to that for the unad- justed markup, although smaller in magnitude and adding considerably less explanatory... ..."