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Open access

Paulo C. Rodrigues

Summary

Genotype-by-environment interaction (GEI) is frequently encountered in multi-environment trials, and represents differential responses of genotypes across environments. With the development of molecular markers and mapping techniques, researchers can go one step further and analyse the whole genome to detect specific locations of genes which influence a quantitative trait such as yield. Such a location is called a quantitative trait locus (QTL), and when these QTLs have different expression across environments we talk about QTL-by-environment interaction (QEI), which is the basis of GEI. Good understanding of these interactions enables researchers to select better genotypes across different environmental conditions, and consequently to improve crops in developed and developing countries. In this paper we present an overview of statistical methods and models commonly used to detect and to understand GEI and QEI, ranging from the simple joint regression model to complex eco-physiological genotype-to-phenotype simulation models.

Open access

Anderson Cristiano Neisse, Jhessica Letícia Kirch and Kuang Hongyu

Summary

The presence of genotype-environment interaction (GEI) influences production making the selection of cultivars in a complex process. The two most used methods to analyze GEI and evaluate genotypes are AMMI and GGE Biplot, being used for the analysis of multi environment trials data (MET). Despite their different approaches, both models complement each other in order to strengthen decision making. However, both models are based on biplots, consequently, biplot-based interpretation doesn’t scale well beyond two-dimensional plots, which happens whenever the first two components don’t capture enough variation. This paper proposes an approach to such cases based on cluster analysis combined with the concept of medoids. It also applies AMMI and GGE Biplot to the adjusted data in order to compare both models. The data is provided by the International Maize and Wheat Improvement Center (CIMMYT) and comes from the 14th Semi-Arid Wheat Yield Trial (SAWYT), an experiment concerning 50 genotypes of spring bread wheat (Triticum aestivum) germplasm adapted to low rainfall. It was performed in 36 environments across 14 countries. The analysis provided 25 genotypes clusters and 6 environments clusters. Both models were equivalent for the dataâĂŹs evaluation, permitting increased reliability in the selection of superior cultivars and test environments.

Open access

Dorah Riah Mabule

Abstract

The aim of this article is to explore the dynamic of language choice and language use as well as to examine the effect of language policy on language attitudes in the Department of Correctional Services (DCS) with special reference to Pretoria Central Prison, now called Kgoši Mampuru Correctional facility where there is some resistance to the use of English as the only official language of business.

A case study was conducted at this facility to find out the language attitudes of the participants towards English as the only official language of business. A questionnaire was used to evoke the participants’ attitudes and beliefs regarding the importance of the use of other official languages (indigenous languages which, like English, also have official status) in their daily lives. A total of 60 correctional services staff and 280 offenders took part in this research study. Interviews and observations were mainly carried out at the research site to triangulate the data. Only the findings from the 280 offenders will be reported in this article.

The findings of this research study show that the participants were keen to use their languages of choice and favoured the language functions of their indigenous languages. The findings suggest that the prevailing language attitudes were in contrast with the aims of language policy at DCS thus making the effect of language planning not to be realized.

Open access

Athanasios Sourmelidis

Abstract

In this paper, we prove a discrete analogue of Voronin’s early finite-dimensional approximation result with respect to terms from a given Beatty sequence and make use of Taylor approximation in order to derive a weak universality statement.

Open access

Dennis Matotoka and Kola O. Odeku

Abstract

In South Africa, progressive laws, policies and institutions established since 1996 seek to proliferate the representation of black African women in the private sector. However, the sector remains stagnant in giving opportunities to black African women to attain and occupy managerial and leadership positions. Black African women are not yet accepted as an integral of part of decision-making in the private sector contrary to the public sector that has somewhat progressed to place black African women in key decision-making positions in government. Consequently, black African women in the private sector predominately dominate the unskilled labour positions. The underrepresentation of black African women essentially denies them of economic participation and equality in the workplace. It is against the backdrop of this underrepresentation that this article analyses salient transformative legislative interventions that have been put in place to foster ample representation of black African women into managerial positions in the private sector. However, the concern is that the current legislative framework in South Africa does not explicitly make it mandatory for the private sector to achieve a specific target of black African women representation at the top management positions. The article showcases that the glass ceiling in the private sector is real and is nurtured by the organizational culture, policies and strategies which promote exclusion. Therefore, effective implementation and enforcement of laws and policies fostering mainstreaming of black African women into top managerial positions will help in breaking down the glass-ceiling. This will become realizable with the cooperation of all stake holders and role players where there is deliberate effort to empower and enhance the skill and capacity of women through quality training and education that will drive and deliver robust career development.

Open access

Hrvoje Jošić and Matej Metelko

Abstract

This paper presents empirical evidence on the validity of the Linder hypothesis in the case of Croatia. According to the Linder hypothesis, one of the new theories of international trade, countries with a similar level of income per capita should trade more. In order to investigate the trade pattern of Croatia's international trade, a panel regression model is formulated including 184 Croatia's import partner countries in the period from 2000 to 2016. The Linder effect was displayed and calculated using the Linder variable expressed as an absolute difference between GDP per capita of the importing and the exporting country. The cross-country panel regression model is estimated using Pooled OLS, Fixed and Random effects models. Results of the analysis have shown that the validity of the Linder hypothesis for Croatia cannot be accepted. Instead, the structure of Croatia's trade is in line with the gravity model of international trade.

Open access

Orietta Luzi, Fabrizio Solari and Fabiana Rocci

Abstract

The Frame SBS is a statistical register which has been developed at the Italian National Statistical Institute to support the annual estimation of structural business statistics (SBS). Actually, a number of core SBS are estimated by combining microdata directly supplied by different administrative sources. In this context, more accurate estimates for those SBS that are not covered by administrative sources can be obtained through small area estimation (SAE). In this article, we illustrate an application of SAE methods in the framework of the Frame SBS register in order to assess the potential advantages that can be achieved in terms of increased quality and reliability of the target variables. Different types of auxiliary information and approaches are compared in order to identify the optimal estimation strategy in terms of precision of the estimates.

Open access

Thomas Zimmermann and Ralf Thomas Münnich

Abstract

The demand for reliable business statistics at disaggregated levels, such as industry classes, increased considerably in recent years. Owing to small sample sizes for some of the domains, design-based methods may not provide estimates with adequate precision. Hence, modelbased small area estimation techniques that increase the effective sample size by borrowing strength are needed. Business data are frequently characterised by skewed distributions, with a few large enterprises that account for the majority of the total for the variable of interest, for example turnover. Moreover, the relationship between the variable of interest and the auxiliary variables is often non-linear on the original scale. In many cases, a lognormal mixed model provides a reasonable approximation of this relationship. In this article, we extend the empirical best prediction (EBP) approach to compensate for informative sampling, by incorporating design information among the covariates via an augmented modelling approach. This gives rise to the EBP under the augmented model. We propose to select the augmenting variable based on a joint assessment of a measure of predictive accuracy and a check of the normality assumptions. Finally, we compare our approach with alternatives in a model-based simulation study under different informative sampling mechanisms.

Open access

Mary H. Mulry, Stephen Kaputa and Katherine J. Thompson

Abstract

Recent research on the use of M-estimation methodology for detecting and treating verified influential values in economic surveys found that initial parameter settings affect effectiveness. In this article, we explore the basic question of how to develop initial settings for the M-estimation parameters. The economic populations that we studied are highly skewed and are consequently highly stratified. While we investigated settings for several parameters, the most challenging problem was to develop an “automatic” data-driven method for setting the initial value of the tuning constant φ, the parameter with the greatest influence on performance of the algorithm. Of all the methods that we considered, we found that methods defined in terms of the accuracy of published estimates can be implemented on a large scale and yielded the best performance. We illustrate the methodology with an empirical analysis of 36 consecutive months of data from 19 industries in the Monthly Wholesale Trade Survey.

Open access

Deirdre Giesen, Mario Vella, Charles F. Brady, Paul Brown, Daniela Ravindra and Anita Vaasen-Otten

Abstract

Managing response burden is key to ensuring an ongoing and efficient supply of fit-forpurpose data. While statistical organizations use multi-faceted approaches to achieve this, response burden management has become an essential element of the strategy used by the U.S. Census Bureau, Statistics New Zealand, Statistics Canada, and Statistics Netherlands. Working in collaboration with respondents, with internal resources dedicated to provide customized approaches for large respondents and with other stakeholders (constituency representatives, associations, etc.) response burden management endeavors to minimize burden and educate stakeholders on the benefit of official statistics. The role continues to evolve with important initiatives regarding the compilation of burden metrics, improvements to existing tracking tools, and an expanded communication role.