Double-Robust Methods

2014 ◽  
pp. 209-236
Keyword(s):  
Robust Methods ◽  
Double Robust

scholarly journals Introduction to Double Robust Methods for Incomplete Data

2018 ◽  
Vol 33 (2) ◽  
pp. 184-197 ◽  
Author(s):  
Shaun R. Seaman ◽  
Stijn Vansteelandt
Keyword(s):  
Incomplete Data ◽  
Robust Methods ◽  
Double Robust

Applying robust methods to operational risk modeling

2006 ◽  
Vol 1 (1) ◽  
pp. 27-41 ◽  
Author(s):  
Anna Chernobai ◽  
Svetlozar Rachev
Keyword(s):  
Operational Risk ◽  
Risk Modeling ◽  
Robust Methods ◽  
Operational Risk Modeling

scholarly journals Impact of Adopting Improved Seeds on Access to Broader Food Groups Among Small-Scale Sorghum Producers in Tanzania

SAGE Open ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 215824402097999
Author(s):  
Aloyce R. Kaliba ◽  
Anne G. Gongwe ◽  
Kizito Mazvimavi ◽  
Ashagre Yigletu
Keyword(s):  
Food Security ◽  
Dietary Diversity ◽  
Sampling Technique ◽  
Inverse Probability Weighting ◽  
Reproductive Age ◽  
Small Scale ◽  
Probability Weighting ◽  
Food Groups ◽  
Inverse Probability ◽  
Double Robust

In this study, we use double-robust estimators (i.e., inverse probability weighting and inverse probability weighting with regression adjustment) to quantify the effect of adopting climate-adaptive improved sorghum varieties on household and women dietary diversity scores in Tanzania. The two indicators, respectively, measure access to broader food groups and micronutrient and macronutrient availability among children and women of reproductive age. The selection of sample households was through a multistage sampling technique, and the population was all households in the sorghum-producing regions of Central, Northern, and Northwestern Tanzania. Before data collection, enumerators took part in a 1-week training workshop and later collected data from 822 respondents using a structured questionnaire. The main results from the study show that the adoption of improved sorghum seeds has a positive effect on both household and women dietary diversity scores. Access to quality food groups improves nutritional status, food security adequacy, and general welfare of small-scale farmers in developing countries. Agricultural projects that enhance access to improved seeds are, therefore, likely to generate a positive and sustainable effect on food security and poverty alleviation in sorghum-producing regions of Tanzania.

Robust methods in analysis of natural language data

2002 ◽  
Vol 8 (2-3) ◽  
pp. 93-96
Author(s):  
AFZAL BALLIM ◽  
VINCENZO PALLOTTA
Keyword(s):  
Information Systems ◽  
Natural Language ◽  
Automated Analysis ◽  
Approximate Analysis ◽  
Robust Methods ◽  
Analysis Techniques ◽  
Intelligent Information Systems ◽  
Recent Interest ◽  
Language Data ◽  
Intelligent Information

The automated analysis of natural language data has become a central issue in the design of intelligent information systems. Processing unconstrained natural language data is still considered as an AI-hard task. However, various analysis techniques have been proposed to address specific aspects of natural language. In particular, recent interest has been focused on providing approximate analysis techniques, assuming that when perfect analysis is not possible, partial results may be still very useful.

scholarly journals Cyclodextrins as Supramolecular Recognition Systems: Applications in the Fabrication of Electrochemical Sensors

Materials ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1668
Author(s):  
Bronach Healy ◽  
Tian Yu ◽  
Daniele C. da Silva Alves ◽  
Cynthia Okeke ◽  
Carmel B. Breslin
Keyword(s):  
Chiral Recognition ◽  
Electrochemical Sensors ◽  
Intramolecular Interactions ◽  
Robust Methods ◽  
Short Introduction ◽  
Reduced Graphene ◽  
Target Analytes ◽  
Recognition Systems ◽  
Covalent Interactions ◽  
Target Analyte

Supramolecular chemistry, although focused mainly on noncovalent intermolecular and intramolecular interactions, which are considerably weaker than covalent interactions, can be employed to fabricate sensors with a remarkable affinity for a target analyte. In this review the development of cyclodextrin-based electrochemical sensors is described and discussed. Following a short introduction to the general properties of cyclodextrins and their ability to form inclusion complexes, the cyclodextrin-based sensors are introduced. This includes the combination of cyclodextrins with reduced graphene oxide, carbon nanotubes, conducting polymers, enzymes and aptamers, and electropolymerized cyclodextrin films. The applications of these materials as chiral recognition agents and biosensors and in the electrochemical detection of environmental contaminants, biomolecules and amino acids, drugs and flavonoids are reviewed and compared. Based on the papers reviewed, it is clear that cyclodextrins are promising molecular recognition agents in the creation of electrochemical sensors, chiral sensors, and biosensors. Moreover, they have been combined with a host of materials to enhance the detection of the target analytes. Nevertheless, challenges remain, including the development of more robust methods for the integration of cyclodextrins into the sensing unit.

Mild, powerful, and robust methods for esterification, amide formation, and thioesterification between acid chlorides and alcohols, amines, thiols, respectively

Tetrahedron ◽  
2007 ◽  
Vol 63 (48) ◽  
pp. 12071-12080 ◽  
Author(s):  
Hidefumi Nakatsuji ◽  
Mami Morimoto ◽  
Tomonori Misaki ◽  
Yoo Tanabe
Keyword(s):  
Acid Chlorides ◽  
Robust Methods ◽  
Amide Formation
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