Neotypifications of Linnaean names in Hybanthus (Violaceae)

Current studies in South American Violaceae detected the necessity of neotypes for Viola calceolaria L. (equivalent to Hybanthus calceolaria (L.) Oken) and Viola oppositifolia L. (equivalent to Hvbanthus oppositifolius (L.) Taub.), names of species originally described in Loefling`s her Hispanicum, but without validly published names.

Disposition of two names in Almeidea (Rutaceae)

(Disposition of two names in Almeidea (Rutaceae)). Examination of type specimens at the P herbarium showed that Almeidea longifolia A. St.-Hil. (Rutaceae) is an illegitimate substitute name for A. affinis A. St.-Hil. The latter name is proposed here as a heterotypic synonym of A. rubra A. St.-Hil.

On estimation and influence diagnostics for log-Birnbaum-Saunders Student-t regression models: Full Bayesian analysis

The purpose of this paper is to develop a Bayesian approach for log-Birnbaum-Saunders Student-t regression models under right-censored survival data. Markov chain Monte Carlo (MCMC) methods are used to develop a Bayesian procedure for the considered model. In order to attenuate the influence of the outlying observations on the parameter estimates, we present in this paper Birnbaum-Saunders models in which a Student-t distribution is assumed to explain the cumulative damage. Also, some discussions on the model selection to compare the fitted models are given and case deletion influence diagnostics are developed for the joint posterior distribution based on the Kullback-Leibler divergence. The developed procedures are illustrated with a real data set. (C) 2010 Elsevier B.V. All rights reserved.

Local influence for Student-t partially linear models

In this paper we extend partial linear models with normal errors to Student-t errors Penalized likelihood equations are applied to derive the maximum likelihood estimates which appear to be robust against outlying observations in the sense of the Mahalanobis distance In order to study the sensitivity of the penalized estimates under some usual perturbation schemes in the model or data the local influence curvatures are derived and some diagnostic graphics are proposed A motivating example preliminary analyzed under normal errors is reanalyzed under Student-t errors The local influence approach is used to compare the sensitivity of the model estimates (C) 2010 Elsevier B V All rights reserved

Bayesian density estimation using Skew Student-t-Normal mixtures

We present a Bayesian approach for modeling heterogeneous data and estimate multimodal densities using mixtures of Skew Student-t-Normal distributions [Gomez, H.W., Venegas, O., Bolfarine, H., 2007. Skew-symmetric distributions generated by the distribution function of the normal distribution. Environmetrics 18, 395-407]. A stochastic representation that is useful for implementing a MCMC-type algorithm and results about existence of posterior moments are obtained. Marginal likelihood approximations are obtained, in order to compare mixture models with different number of component densities. Data sets concerning the Gross Domestic Product per capita (Human Development Report) and body mass index (National Health and Nutrition Examination Survey), previously studied in the related literature, are analyzed. (c) 2008 Elsevier B.V. All rights reserved.

Community College Student and Faculty Information Needs and Information Seeking: an Ethnographic Study

This presentation was offered as part of the CUNY Library Assessment Conference, Reinventing Libraries: Reinventing Assessment, held at the City University of New York in June 2014.

Assessment as Engagement, Assessment as Outreach: Understanding Student Learning About Research at the Trinity College Library

This presentation was offered as part of the CUNY Library Assessment Conference, Reinventing Libraries: Reinventing Assessment, held at the City University of New York in June 2014.

Air Conditioning and Refrigeration Student Looking at Plans

A student from the New York Trade School in the Air Conditioning and Refrigeration Dept. looks at plans on top of a building. Black and white photograph contains some damage from adhesive and writing on the front.

Student at work with closed-circuit TV

A student in the Closed-circuit TV Dept. at the New York Trade School is shown working. Black and white photograph.

Closed-circuit Television Student Working

A student is show working with closed-circuit television at the New York Trade School. Black and white photograph.

Data Processing Student Working

A student from the Data Processing program at the New York Trade School is shown working. Black and white photograph with some edge damage due to writing in black along the top.

Professor and Student in Piano Crafts Department

Here a professor in the Piano Crafts Department at the New York Trade School is shown helping a student. Black and white photograph.

Welding Student at Work

A student in the Welding Department at the New York Trade School is pictured working. Notice the sparks that are being emitted from the equipment. Black and white photograph.

Sign Painting Student Working Outside

A Sign Painting student from the New York Trade School is pictured working outside on scaffolding on an AMOCO sign. Black and white photograph.