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Table 3.5: Indonesia production function, average productivity of irrigated land, 1971-98 Model C Model D

in Determinants of Agricultural Growth in Indonesia, the Philippines, and Thailand
by Yair Mundlak, Donald F. Larson, Rita Butzer, Jerusalem Donald, F. Larson, Masayoshi Honma, Toshihiko Kawagoe, William Cuddihy
"... In PAGE 30: ... The public goods grew constantly. The strong trend in the variables is reflected in the correlation between the variables as can be seen in the correlation matrix in Table3 -A. Because of this correlation, the number of linear combination of the variables (principal components) needed to exhaust the information embedded in the regressors is rather sma ll.... In PAGE 31: ... There are two possible explanations for this relatively weak effect of the price variables: First, the price does not matter at all. This is not supported by the data because, as shown in Table3 A, the correlation between output and the wholesale price measure is 0.73.... In PAGE 31: ...73. Second, Table3 A shows that the inputs are also correlated with the price. It is therefore likely that much of the contribution of prices is channeled through the inputs, and it is the net direct effect of the price that is weak.... In PAGE 31: ... The reduction in the land elasticities is compensated by the increase in the labor elasticity. The correlation coefficient of labor with irrigated land and with capital is high ( Table3 A), and this may cause the variability in the estimates. Another striking difference from the results for the other two countries is the low capital elasticity.... In PAGE 66: ...84 1.00 Table3 -A: Correlation matrix for Indonesia variables, 1971-98 Output Irrigated land Rain-fed land Fertilizer Capital Labor Wholesale price ratio Price spread No education Roads Infant mortality Output 1.000 Irrigated land 0.... ..."

Table 3 Cluster accuracy and stability on the completely synthetic data with four repeated measurements at high noise level

in Software Clustering gene-expression data with repeated measurements
by Ka Yee Yeung, Mario Medvedovic, Open Access, Roger E Bumgarner 2003
"... In PAGE 7: ...cluster quality over the approach of averaging over repeated measurements using the same algorithms at high noise level. In terms of cluster stability (see Table3 b), the following three approaches yield average adjusted Rand index above 0.900: the elliptical model of the IMM approach; the comment reviews reports deposited research interactions information refereed research http://genomebiology.... ..."

Table 2 Cluster accuracy and stability on the completely synthetic data with four repeated measurements at low noise level

in Software Clustering gene-expression data with repeated measurements
by Ka Yee Yeung, Mario Medvedovic, Open Access, Roger E Bumgarner 2003
"... In PAGE 6: ... The external knowledge is not used in computing cluster stability. Completely synthetic data at low noise level Table2 a,b shows selected results on cluster accuracy and cluster stability on the completely synthetic datasets with four simulated repeated measurements. Table 2a,b show results from average linkage, complete linkage and centroid linkage hierarchical algorithms, k-means, MCLUST-HC (a hierarchical model-based clustering algorithm from MCLUST) and IMM.... In PAGE 6: ... Completely synthetic data at low noise level Table 2a,b shows selected results on cluster accuracy and cluster stability on the completely synthetic datasets with four simulated repeated measurements. Table2 a,b show results from average linkage, complete linkage and centroid linkage hierarchical algorithms, k-means, MCLUST-HC (a hierarchical model-based clustering algorithm from MCLUST) and IMM. Both single linkage and DIANA produce very low-quality and unstable clusters and their adjusted Rand indices are not shown.... ..."

Table 3. RDFS Constructs HDM Representation

in Representing RDF and RDF Schema in the HDM
by Ra Poulovassilis, Alexandra Poulovassilis, Dean Williams, Dean Williams 2002
"... In PAGE 9: ... 4. Components of RDF Schema 6 Representing RDF Schema in the HDM Table3 speci es RDF Schema in the HDM. We see that there are two di erent modelling constructs: RDFSNode and RDFSEdge with, respectively, 3 and 7 in- stances (as with RDF, this schema will be the same for all RDFS data sources).... In PAGE 9: ... We see that there are two di erent modelling constructs: RDFSNode and RDFSEdge with, respectively, 3 and 7 in- stances (as with RDF, this schema will be the same for all RDFS data sources). The set of primitiveschema transformations generated for these two constructs are { addRDFSNode(scheme,query) { deleteRDFSNode(scheme,query) { extendRDFSNode(scheme,query) { contractRDFSNode(scheme,query) { renameRDFSNode(scheme,new-name) where the `scheme apos; parameter can be one of the 3 RDFSNode schemes listed in Table3 , and... In PAGE 10: ...scheme: hhrdfs:subProperty,rdfs:Property,rdfs:Propertyii constraint: - construct:RDFSEdge edge: hhrdfs:seeAlso,rdfs:Resource,rdfs:Resourceii scheme: hhrdfs:seeAlso,rdfs:Resource,rdfs:Resourceii constraint: - construct:RDFSEdge edge: hhrdfs:isDe nedBy,rdfs:Resource,rdfs:Resourceii scheme: hhrdfs:isDe nedBy,rdfs:Resource,rdfs:Resourceii constraint: - Table3 . De nition of RDFS model constructs 7 An Example An example of an RDF Schema and an instance of data complying to this schema is now given, together with the graphs the XML documents representandthe HDM instances required to store the data.... ..."

Table 1. Description of the Constraint class

in An Extensible Modelling Framework for the
by Examination Timetabling Problem, David Ranson, Samad Ahmadi 2006
"... In PAGE 7: ...ig. 4. The classes present in the Constraint Satisfaction Model Constraints are modelled as functional classes. Each Constraint implements the methods shown in Table1 . The getViolationCount() method contains the logic for specifying the Constraint.... ..."
Cited by 1

Table 1. Constraints on the class of models of L.

in Rights and commitments in multi-agent agreements
by Timothy J. Norman, Carles Sierra, Nick R. Jennings 1998
Cited by 16

Table 1. Constraints on the class of models of L.

in Rights and commitments in multi-agent agreements
by Timothy J. Norman, Carles Sierra, Nick R. Jennings 1998
Cited by 16

Table 1. Constraints on the class of models of L.

in Rights and commitments in multi-agent agreements
by Timothy J. Norman, Carles Sierra, Nick R. Jennings 1998
Cited by 16

Table 1. Constraint Data

in Constrained Camera Parameter Estimation and 3D Points Reconstruction from a Single Image
by Qiang Ji, Robert M. Haralick
"... In PAGE 8: ... From the model, a total of 4 geometric constraints are selected regarding the pass points. Table1 summarizes the constraints used. Table 1.... ..."

Table 25: Labor Index69

in unknown title
by unknown authors
"... In PAGE 7: ...able 24 Fixed Operating Costs.................................................................................................................52 Table25 Labor Index.... In PAGE 59: ...5% $2,154,000 Of total installed cost Model: R9906A, 1997 $ The salaries are on a 1998 basis and will need to be indexed to other cost years when appropriate. The index to adjust these costs is taken from the Bureau of Labor Statistics69 and is given in Table25 . As with the other indexes, data were available only up until 1996.... ..."
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