Testing common nonlinear features in vector nonlinear autoregressive models

This paper studies a special class of vector smooth-transition autoregressive (VSTAR) models that contains common nonlinear features (CNFs), for which we proposed a triangular representation and developed a procedure of testing CNFs in a VSTAR model. We first test a unit root against a stable STAR process for each individual time series and then examine whether CNFs exist in the system by Lagrange Multiplier (LM) test if unit root is rejected in the first step. The LM test has standard Chi-squared asymptotic distribution. The critical values of our unit root tests and small-sample properties of the F form of our LM test are studied by Monte Carlo simulations. We illustrate how to test and model CNFs using the monthly growth of consumption and income data of United States (1985:1 to 2011:11).

Residual-based Inference for Common Nonlinear Features

This paper investigates common nonlinear features in multivariate nonlinear autore-gressive models via testing the estimated residuals. A Wald-type test is proposed and itis asymptotically Chi-squared distributed. Simulation studies are given to examine thefinite-sample properties of the proposed test.

Common Features in Vector Nonlinear Time Series Models

This thesis consists of four manuscripts in the area of nonlinear time series econometrics on topics of testing, modeling and forecasting nonlinear common features. The aim of this thesis is to develop new econometric contributions for hypothesis testing and forecasting in these area. Both stationary and nonstationary time series are concerned. A definition of common features is proposed in an appropriate way to each class. Based on the definition, a vector nonlinear time series model with common features is set up for testing for common features. The proposed models are available for forecasting as well after being well specified. The first paper addresses a testing procedure on nonstationary time series. A class of nonlinear cointegration, smooth-transition (ST) cointegration, is examined. The ST cointegration nests the previously developed linear and threshold cointegration. An Ftypetest for examining the ST cointegration is derived when stationary transition variables are imposed rather than nonstationary variables. Later ones drive the test standard, while the former ones make the test nonstandard. This has important implications for empirical work. It is crucial to distinguish between the cases with stationary and nonstationary transition variables so that the correct test can be used. The second and the fourth papers develop testing approaches for stationary time series. In particular, the vector ST autoregressive (VSTAR) model is extended to allow for common nonlinear features (CNFs). These two papers propose a modeling procedure and derive tests for the presence of CNFs. Including model specification using the testing contributions above, the third paper considers forecasting with vector nonlinear time series models and extends the procedures available for univariate nonlinear models. The VSTAR model with CNFs and the ST cointegration model in the previous papers are exemplified in detail,and thereafter illustrated within two corresponding macroeconomic data sets.

Benchmark Evaluation of HOG Descriptors as Features for Classification of Traffic Signs

The purpose of this paper is to analyze the performance of the Histograms of Oriented Gradients (HOG) as descriptors for traffic signs recognition. The test dataset consists of speed limit traffic signs because of their high inter-class similarities.   HOG features of speed limit signs, which were extracted from different traffic scenes, were computed and a Gentle AdaBoost classifier was invoked to evaluate the different features. The performance of HOG was tested with a dataset consisting of 1727 Swedish speed signs images. Different numbers of HOG features per descriptor, ranging from 36 features up 396 features, were computed for each traffic sign in the benchmark testing. The results show that HOG features perform high classification rate as the Gentle AdaBoost classification rate was 99.42%, and they are suitable to real time traffic sign recognition. However, it is found that changing the number of orientation bins has insignificant effect on the classification rate. In addition to this, HOG descriptors are not robust with respect to sign orientation.

Professional and Non-Professional Written Travel Texts – Do They Have Common Features? : A Comparative Investigation on Travel Texts on Trysil, Norway

This study aims to investigate possible distinctions between professional and non-professional written travel texts all treating the same destination: the Norwegian ski resort Trysil. The study will investigate to what extent the different texts correlate with the genre of travel texts, as the travel texts are treated as personal narratives, and how they conform to a given structure for narratives and with guidelines for professional writers. Furthermore, the investigation aims to explore to what extent there are similarities and differences between the texts regarding the given structure. The texts will first be analysed and organized separately by macrorules and a news schema that are constructed specifically for these sorts of texts, in order to reveal their discourse structure, and then compared to each other. As the discourse structure of the different texts is revealed, it is seen that there are certain differences between the two different text types. Finally, seen that the text types differ in their structure, this study will show that despite the fact that journalists write stories, and that non-professional written stories are narratives, they do not share the same structure, and are constructed in different ways.

Estimating sectoral cycles using cointegration and common features

This paper investigates the degree of short run and long run co-movement in U.S. sectoral output data by estimating sectoraI trends and cycles. A theoretical model based on Long and Plosser (1983) is used to derive a reduced form for sectoral output from first principles. Cointegration and common features (cycles) tests are performed; sectoral output data seem to share a relatively high number of common trends and a relatively low number of common cycles. A special trend-cycle decomposition of the data set is performed and the results indicate a very similar cyclical behavior across sectors and a very different behavior for trends. Indeed. sectors cyclical components appear as one. In a variance decomposition analysis, prominent sectors such as Manufacturing and Wholesale/Retail Trade exhibit relatively important transitory shocks.

The importance of common cyclical features in VAR analysis: a Monte-Carlo study

Despite the commonly held belief that aggregate data display short-run comovement, there has been little discussion about the econometric consequences of this feature of the data. We use exhaustive Monte-Carlo simulations to investigate the importance of restrictions implied by common-cyclical features for estimates and forecasts based on vector autoregressive models. First, we show that the ìbestî empirical model developed without common cycle restrictions need not nest the ìbestî model developed with those restrictions. This is due to possible differences in the lag-lengths chosen by model selection criteria for the two alternative models. Second, we show that the costs of ignoring common cyclical features in vector autoregressive modelling can be high, both in terms of forecast accuracy and efficient estimation of variance decomposition coefficients. Third, we find that the Hannan-Quinn criterion performs best among model selection criteria in simultaneously selecting the lag-length and rank of vector autoregressions.

The importance of Common-Cyclical Features in VAR analysis: a Monte-Carlo study (Preliminary Version)

Despite the belief, supported byrecentapplied research, thataggregate datadisplay short-run comovement, there has been little discussion about the econometric consequences ofthese data “features.” W e use exhaustive M onte-Carlo simulations toinvestigate theimportance ofrestrictions implied by common-cyclicalfeatures for estimates and forecasts based on vectorautoregressive and errorcorrection models. First, weshowthatthe“best” empiricalmodeldevelopedwithoutcommoncycles restrictions neednotnestthe“best” modeldevelopedwiththoserestrictions, duetothe use ofinformation criteria forchoosingthe lagorderofthe twoalternative models. Second, weshowthatthecosts ofignoringcommon-cyclicalfeatures inV A R analysis may be high in terms offorecastingaccuracy and e¢ciency ofestimates ofvariance decomposition coe¢cients. A lthough these costs are more pronounced when the lag orderofV A R modelsareknown, theyarealsonon-trivialwhenitis selectedusingthe conventionaltoolsavailabletoappliedresearchers. T hird, we…ndthatifthedatahave common-cyclicalfeatures andtheresearcherwants touseaninformationcriterium to selectthelaglength, theH annan-Q uinn criterium is themostappropriate, sincethe A kaike and theSchwarz criteriahave atendency toover- and under-predictthe lag lengthrespectivelyinoursimulations.

Using common features to understand the behavior of metal-commodity prices and forecast them at different horizons

The objective of this article is to study (understand and forecast) spot metal price levels and changes at monthly, quarterly, and annual horizons. The data to be used consists of metal-commodity prices in a monthly frequency from 1957 to 2012 from the International Financial Statistics of the IMF on individual metal series. We will also employ the (relatively large) list of co-variates used in Welch and Goyal (2008) and in Hong and Yogo (2009) , which are available for download. Regarding short- and long-run comovement, we will apply the techniques and the tests proposed in the common-feature literature to build parsimonious VARs, which possibly entail quasi-structural relationships between different commodity prices and/or between a given commodity price and its potential demand determinants. These parsimonious VARs will be later used as forecasting models to be combined to yield metal-commodity prices optimal forecasts. Regarding out-of-sample forecasts, we will use a variety of models (linear and non-linear, single equation and multivariate) and a variety of co-variates to forecast the returns and prices of metal commodities. With the forecasts of a large number of models (N large) and a large number of time periods (T large), we will apply the techniques put forth by the common-feature literature on forecast combinations. The main contribution of this paper is to understand the short-run dynamics of metal prices. We show theoretically that there must be a positive correlation between metal-price variation and industrial-production variation if metal supply is held fixed in the short run when demand is optimally chosen taking into account optimal production for the industrial sector. This is simply a consequence of the derived-demand model for cost-minimizing firms. Our empirical evidence fully supports this theoretical result, with overwhelming evidence that cycles in metal prices are synchronized with those in industrial production. This evidence is stronger regarding the global economy but holds as well for the U.S. economy to a lesser degree. Regarding forecasting, we show that models incorporating (short-run) commoncycle restrictions perform better than unrestricted models, with an important role for industrial production as a predictor for metal-price variation. Still, in most cases, forecast combination techniques outperform individual models.

Using common features to understand the behavior of metal-commodity prices and forecast them at different horizons

The objective of this article is to study (understand and forecast) spot metal price levels and changes at monthly, quarterly, and annual frequencies. Data consists of metal-commodity prices at a monthly and quarterly frequencies from 1957 to 2012, extracted from the IFS, and annual data, provided from 1900-2010 by the U.S. Geological Survey (USGS). We also employ the (relatively large) list of co-variates used in Welch and Goyal (2008) and in Hong and Yogo (2009). We investigate short- and long-run comovement by applying the techniques and the tests proposed in the common-feature literature. One of the main contributions of this paper is to understand the short-run dynamics of metal prices. We show theoretically that there must be a positive correlation between metal-price variation and industrial-production variation if metal supply is held fixed in the short run when demand is optimally chosen taking into account optimal production for the industrial sector. This is simply a consequence of the derived-demand model for cost-minimizing firms. Our empirical evidence fully supports this theoretical result, with overwhelming evidence that cycles in metal prices are synchronized with those in industrial production. This evidence is stronger regarding the global economy but holds as well for the U.S. economy to a lesser degree. Regarding out-of-sample forecasts, our main contribution is to show the benefits of forecast-combination techniques, which outperform individual-model forecasts - including the random-walk model. We use a variety of models (linear and non-linear, single equation and multivariate) and a variety of co-variates and functional forms to forecast the returns and prices of metal commodities. Using a large number of models (N large) and a large number of time periods (T large), we apply the techniques put forth by the common-feature literature on forecast combinations. Empirically, we show that models incorporating (short-run) common-cycle restrictions perform better than unrestricted models, with an important role for industrial production as a predictor for metal-price variation.

Biological features of a puzzling symbiotic association between the hermit crab Dardanus insignis and the porcellanid crab Porcellana Sayana (Crustacea)

The symbiotic lifestyle is widespread among porcellanid crabs, which maintain ecological and co-evolutionary associations with annelid polychaetes, poriferans, cnidarians, echinoderms, gastropod. mollusks, and other crustaceans such as shrimps and hermit crabs, among others. We investigated the ecological association between the hermit crab Dardanus insignis and the porcellanid Porcellana sayana, in southeastern Brazil. Porcellanid crabs, hermit crabs, and available shells were collected monthly from July 2001 to June 2003, with a shrimp boat equipped with two double-rig trawl nets. The majority of P. sayana specimens were collected in shells occupied by D. insignis (96.6%); a few were found in empty shells (3.4%). The catch of both symbionts and hosts increased with increasing depth, with the highest occurrence at 35 m. The F. sayana crabs of various sizes could be found solitary or forming aggregations of up to 14 individuals per host, showing no sex or size segregation. In spite of the high diversity of shell species occupied by the hermit crabs and also available in the field, only a few of them were also utilized by P. sayana. The majority (93%) of shells utilized by P. sayana also hosted other symbiont species, constituting the basis of extensive symbiotic complexes. Thus, the ecological relationship between D. insignis and P. sayana may be classified as a non-obligate and non-specific symbiosis that may also involve other facultative organisms such as sea anemones. (C) 2008 Elsevier B.V. All rights reserved.

Structural features of the epididymal region of the domestic duck (Anas plathyrynchos)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

New features of Cuban endemic Pinguicula filifolia (Lentibulariaceae) and considerations on its habitat and ecology

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

The use of software Mapavox for teaching graphics and games to blind and low vision students: a development through practices

Current policies on education to visually impaired point for a growing trend of including students with special educational needs in regular schools. However, most often this inclusion is not accompanied by an appropriate professional trained or infrastructure, which has been presented as a big problem for regular school teachers who have students with visual impairments in their classroom. Based on this situation, the Group of Extension in Tactile Cartography from UNESP - University of the State of São Paulo - Campus de Rio Claro - SP - Brazil has been developing educational material of geography and cartography to blind students at a special school. Among the materials developed in this study highlight the development of graphics and board games provided with sound capabilities through MAPAVOX, software developed in partnership with UFRJ - Federal University from Rio de Janeiro - RJ - Brazil. Through this software, sound capabilities can be inserted into built materials, giving them a multi-sensory character. In most cases the necessary conditions for building specific materials to students with visual impairments is expensive and beyond the reach of features from a regular school, so the survey sought to use easy access and low cost materials like Cork, leaf aluminum, material for fixing and others. The development of these materials was supported by preparation in laboratory and its subsequent test through practices involving blind students. The methodology used on the survey is based on qualitative research and non comparative analysis of the results. In other words, the material is built based on the special students perception and reality construction, not being mere adaptations of visual materials, but a construction focused on the reality of the visually impaired. The results proved were quite successful as the materials prepared were effective on mediating the learning process of students with disabilities. Geographical and cartographic concepts were seized by the students through the technology used, associated with the use of materials that took into account in its building process the perception of the students.

Microscopic features of tick-bite lesions in anteaters and armadillos - Emas National Park and the Pantanal region of Brazil

The naturally occurring wildlife host associations between ticks and tick-borne pathogens found in the neotropics are poorly described. Understanding tick-bite lesions is important as these are the site of host reaction to and pathogen delivery by ticks. As part of a comprehensive study concerning established and emerging tick-host relationships. The present work describes some aspects of tick-bite lesions in anteaters and armadillos captured at the Emas National Park and the Pantanal region of Brazil. Biopsies were of skin were taken and examine. Tick feeding sites of all animals displayed an eosinophilic homogeneous mass, the cement cone, and, occasionally, a feeding cavity underneath the tick attachment site. At these locations the epidermis was usually thickened due to keratinocyte hyperplasia. The main dermal changes included tissue infiltration with a varying number of inflammatory cells, edema, hemorrhage. and vascular dilatation. Cellular infiltration of the dermis was predominantly composed of mononuclear cells, neutrophils. and eosinophils. Mast cells were also seen in both non-parasitized and parasitized skin but were found in higher numbers at perivascular sites and in parasitized skin. Basophils were not seen at tick attachment sites of anteaters or armadillos.