This paper presents the R package anacor for the computation of simple and canonical correspondence analysis with missing values. The canonical correspondence analysis is specified in a rather general way by imposing covariates on the rows and/or the columns of the two-dimensional frequency table. The package allows for scaling methods such as standard, Benzécri, centroid, and Goodman scaling. In addition, along with well-known two- and three-dimensional joint plots including confidence ellipsoids, it offers alternative plotting possibilities in terms of transformation plots, Benzécri plots, and regression plots.

The Laguna Madre is a hypersaline lagoon. Despite harsh conditions, the upper Laguna Madre (ULM) is a highly productive ecosystem and a popular sportfishing area, especially for spotted seatrout and red drum. It is also the most important Texas bay for commercial fishing of black drum. TPWD’s Coastal Fisheries division began conducting routine monitoring of coastal fishery resources in 1977 to guide management. The goal of the present study was to improve understanding of spatiotemporal trends in relative abundance of selected fish and macro-invertebrate species in the upper Laguna Madre. I used TPWD’s bag-seine and water-quality data from the years 1985-2004 to examine variation in species’ relative abundances and relationships to several environmental factors. I hypothesized that one or more of these variables, alone or in combination, were related to spatial and temporal trends in community composition. I used detrended correspondence analysis (DCA) to measure species turnover (beta diversity) and to determine which model (linear or unimodal) of species response along a gradient to apply. I used canonical correspondence analysis to relate species abundances directly to explanatory variables. The explanatory variables were tested for significance and the variance partitioned among three groupings: temporal, spatial and environmental. DCA indicated complete species turnover along two dimensions: seasonal and spatial. It also indicated that a unimodal method such as CCA was appropriate for further analysis. The CCA model included 39 variables. The included variables explained 14% of the variation in species abundance in the data set. Since the first four axes explained 67% of the variation contained in the first two DCA axes, the chosen explanatory variables were sufficient to explain the majority of the tractable variation in species abundance. The variance partitioning procedure indicated that temporal effects were the most important in explaining species variation in the Upper Laguna, followed by the spatial component. The pure environmental component explained the least amount of variation. In this study, much of the variability in species abundance was due to the spawning patterns of estuary-dependent species, most of which spawn in the spring and summer months, leading to higher abundances from spring through fall.

Human activities, such as agricultural activity, housing construction, forest logging, etc., play an important role in vegetation changes. Any disturbance to the ecosystem by a severe change in landscape patterns may reduce the survival capacity of certain plant species. In recent years, many studies have used a geographic information system to establish spatial data on vegetation changes; this information includes both the plant species and their spatial structure. Therefore, the aim of this study is to investigate the trends and patterns of vegetation changes and the degree of correlation with the particular environmental features at Wangan Island and Chimei Island in the Penghu Islands, from 1979 to 2009. Both islands have very similar natural features, including geographic location, natural environment, and economic development, but the spatial structures of the land use type are different. The study makes use of geographic information systems, detrended correspondence analysis, canonical correspondence analysis and landscape ecological indicators as study tools. The results are expected to promote our understanding of the spatial distribution patterns of vegetation types and plant species. The results can be divided into three areas. First, both islands follow the same trend with regard to changes in land cover, but the rates of change are different. And the spatial structure of land use types affects the location of land cover types. Example, the centralized and decentralized villages both impact the distribution of the woodland. The mesh and ring road both impact the location of agricultural land. Second, the grassland plant species are correlated with the environmental factors, but the forest plant species are not. The major woodland specie is Leucaena leucocephala on both islands, whose physiological habits may reduce the degree of the correlation. Third, compared to the two islands, Chimei Island is more significant about that the vegetation types are correlated with the neighboring land use types. Finally, the plant species of the local vegetation types could be predicted by changes in the type of land use. In addition, this study has built a trend scheme of the spatial structure changes on Wangan Island and on Chimei Island, which can be used in the island¡¦s future environmental planning.

This thesis draws upon modern consumption theory to provide an interpretive research framework for examining material culture and consumer behaviour in the Roman world. This approach is applied to data from twelve Pompeian households to identify patterns of consumption, materiality, and motivations for the acquisition of commodities. Analysis of the assemblage data is performed at multiple levels comprising weighted ranking of goods and the application of Correspondence Analysis, with investigation performed on both functional categories and artefact types. Setting the results against theories of consumption and rationality, consumer choice in the ancient world is examined. From this detailed examination of twelve Pompeian houses, ‘core’ and ‘fringe’ commodities and recurring suites of goods are identified. Non-luxury goods are given particular attention as they provide information concerning the consumption of everyday utility objects. This approach also allows the evaluation of statements about the state of occupation of houses in sites such as Pompeii. The results validate this form of analysis as an important tool for assessing the role of the consumer in economies of the ancient world, moving beyond concepts of conspicuous consumption and group values. This research provides a structured interpretive framework upon which varied archaeological data can be superimposed to interrogate the motivations behind commodity acquisition. This research also raises the potential for future consumption modelling using multivariate statistics. Through the application of consumer theory to Roman data, discussion of ancient economies is shifted away from a focus on production to one of demand, choice, and sites of consumption.

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2012 Joint 6th International Conference on Soft Computing and Intelligent Systems (SCIS) and 13th International Symposium on Advanced Intelligent Systems (ISIS) (SCIS-ISIS 2012). November 20-24, 2012, Kobe, Japan

The aim of the diploma thesis was to create independently an application, automating a correspondence analysis calculation using MS Excel and taking advantage of VBA programming language. The application was then used to analyse Slovak banking sector. The created application is based on macro sets which can be split up to two parts. The first part produces a contingency table and converts it into a format usable in the second part. Then there is executed the Correspondence Analysis calculation itself. Supplement Matrix is being used, that allows to discharge functions from matrix and linear algebra. The application allows to process any matrix dimension. Dialog window offers four normalization types, shortened and also full output and it is possible to display row or column variable categories, eventually both. The analysis subject was to find out which of the products are typical for considered banks and for which clients, divided into age categories, is attractive particular bank and/or product. A starting point is a product usage data matrix at a particular bank. There was made a conclusion, that it is possible to divide banks into more traditional or modern type institutions and also that each bank has a typical product.

It is common in cross-cultural research to treat variables as if they have interval scale properties irrespective of how these scales were constructed. The purpose of this research is to explore the differences in and consequences of how respondents from different countries use the same scales over the same scale items. Previously collected data from four countries using the same 6-point verbal and 10-point numeric rating scales were used. The data was rescaled using the delta chi-square and correspondence analysis techniques (Bendixen & Yurova, 2012). The differences in means of the variables were compared in pairs for raw and rescaled data. Bootstrapping was used to estimate confidence intervals of the differences between raw and rescaled values. Furthermore, a method of partitioning the differences in means into rescaling and cultural components was devised. In 83.3% and 94.9% of the cases, the differences in raw versus rescaled means were significant at the 5% level for verbal and numeric variables respectively. The results of partitioning indicate that by not rescaling the data, the differences in raw means consistently exaggerate the true cultural differences: the extracted cultural component was underestimated by 12.8% on average for verbal variables and by 5.3% for numeric variables. Therefore, reporting the differences in raw means as a true reflection of cultural differences is in error. Finally, the effect of rescaling in pancultural research was investigated by comparing the factor structure of doubly standardized raw and rescaled data. Pancultural research attempts to identify etic, or universal, dimensions of human culture and employs double standardization to remove cultural and individual biases inherent to cross-cultural data. While no differences in latent factors extracted were found for raw and rescaled data, considerable differences in the variance explained and slight differences in factor structure were found for double standardized rescaled and double standardized raw data. The results of this research indicate that researchers and practitioners in the field of cross-cultural research should choose their scales very carefully. Furthermore, to extract true cultural differences it is probably necessary to rescale and partition differences in means. Further research on the impact of rescaling is proposed.

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