Ideal for particularly small areas

OPE Journal ◽  
2021 ◽  
Vol 11 (34) ◽  
pp. 30-30
Keyword(s):  
Small Area ◽  
Fill Factor ◽  
Small Areas

Dracula Technologies (Valence, France) has achieved a new fill factor record for an OPV module with fully inkjet-printed layers. These small-area modules target indoor applications

Improving the quality of disaggregated SDG indicators with cluster information for small area estimates

2020 ◽  
Vol 36 (4) ◽  
pp. 955-961
Author(s):  
Rizky Zulkarnain ◽  
Dwi Jayanti ◽  
Tri Listianingrum
Keyword(s):  
Small Area ◽  
Research University ◽  
Direct Method ◽  
Random Effect ◽  
Auxiliary Information ◽  
District Level ◽  
Small Areas ◽  
Associate Dean ◽  
Development Goals

The increasing needs for more disaggregated data motivates National Statistical Offices (NSOs) to develop efficient methods for producing official statistics without compromising on quality. In Indonesia, regional autonomy requires that Sustainable Development Goals (SDGs) indicators are available up to the district level. However, several surveys such as the Indonesian Demographic and Health Survey produce estimates up to the provincial level only. This generates gaps in support for district level policies. Small area estimation (SAE) techniques are often considered as alternatives for overcoming this issue. SAE enables more reliable estimation of the small areas by utilizing auxiliary information from other sources. However, the standard SAE approach has limitations in estimating non-sampled areas. This paper introduces an approach to estimating the non-sampled area random effect by utilizing cluster information. This model is demonstrated via the estimation of contraception prevalence rates at district levels in North Sumatera province. The results showed that small area estimates considering cluster information (SAE-cluster) produce more precise estimates than the direct method. The SAE-cluster approach revises the direct estimates upward or downward. This approach has important implications for improving the quality of disaggregated SDGs indicators without increasing cost. The paper was prepared under the kind mentorship of Professor James J. Cochran, Associate Dean for Research, Prof. of Statistics and Operations Research, University of Alabama.

scholarly journals 17.2% efficiency CuIn1−xGaxSe2 thin-film based mini-module thanks to alternative architecture yielding 81% fill factor

2019 ◽  
Vol 10 ◽  
pp. 4
Author(s):  
Justine Lorthioir ◽  
Ludovic Arzel ◽  
Stéphane Ginestar ◽  
Lionel Assmann ◽  
Nicolas Barreau
Keyword(s):  
Thin Film ◽  
Small Area ◽  
Output Voltage ◽  
Fill Factor ◽  
Promising Result ◽  
Fabrication Process ◽  
Module Structure ◽  
Standard Cell ◽  
In Series

An alternative to conventional Cu(In,Ga)Se2 module structure is proposed and experimentally investigated. This alternative module structure, which consists in applying metallic buses to connect monolithically adjacent cells in series, is likely to offer the opportunity of minimizing both optical and electrical losses observed in conventional module structure compared to small area cells. The fabrication process of such alternative modules is presented. The performances achieved are discussed in comparison with a standard small-area-cell elaborated simultaneously. Despite slightly lower output voltage per cell, the alternative module structure demonstrates an efficiency of 17.2% (with 81% fill factor), against 16.4% (with 75% fill factor) for the standard cell. This promising result opens new routes to decrease the gap observed between small-area-cells and industrial modules.

scholarly journals Bayesian Predictive Inference of a Proportion Under a Twofold Small-Area Model

2016 ◽  
Vol 32 (1) ◽  
pp. 187-208 ◽  
Author(s):  
Balgobin Nandram
Keyword(s):  
Binary Data ◽  
Small Area ◽  
Finite Population ◽  
Independent Random Variables ◽  
Subsequent Stage ◽  
Intracluster Correlation ◽  
Binary Responses ◽  
Small Areas ◽  
Area Model ◽  
The Third

Abstract We extend the twofold small-area model of Stukel and Rao (1997; 1999) to accommodate binary data. An example is the Third International Mathematics and Science Study (TIMSS), in which pass-fail data for mathematics of students from US schools (clusters) are available at the third grade by regions and communities (small areas). We compare the finite population proportions of these small areas. We present a hierarchical Bayesian model in which the firststage binary responses have independent Bernoulli distributions, and each subsequent stage is modeled using a beta distribution, which is parameterized by its mean and a correlation coefficient. This twofold small-area model has an intracluster correlation at the first stage and an intercluster correlation at the second stage. The final-stage mean and all correlations are assumed to be noninformative independent random variables. We show how to infer the finite population proportion of each area. We have applied our models to synthetic TIMSS data to show that the twofold model is preferred over a onefold small-area model that ignores the clustering within areas. We further compare these models using a simulation study, which shows that the intracluster correlation is particularly important.

scholarly journals MEMODELKAN TINGKAT PENGANGGURAN DI KOTA DENPASAR DENGAN PENDUGAAN AREA KECIL EMPIRICAL BAYES

2021 ◽  
Vol 10 (2) ◽  
pp. 81
Author(s):  
REYNALDO PANJI WICAKSONO ◽  
I KOMANG GDE SUKARSA ◽  
I PUTU EKA NILA KENCANA
Keyword(s):  
Economic Development ◽  
Unemployment Rate ◽  
Small Area ◽  
Empirical Bayes ◽  
Small Area Estimation ◽  
Economic Conditions ◽  
Small Areas ◽  
Area Estimation ◽  
Direct Estimation ◽  
Selection Of

Economic development are described by the unemployment rate. The higher unemployment rate, the weaker economic conditions. Nowadays more policies require information on small areas. The direct estimation does not provide accurate results in smaller areas. Thus the small area estimation becomes an alternative to estimate the parameters. The accuracy depends on the selection of the predictors. In 2019, the unemployment rate in Denpasar is 2,22%. The result shows that the unemployment rate in each district in Denpasar varies from 0,1% to 0,3%

Estimating and projecting the populations of urban communities

1994 ◽  
Vol 26 (11) ◽  
pp. 1671-1697 ◽  
Author(s):  
P Rees
Keyword(s):  
User Interface ◽  
Urban Communities ◽  
Demographic Change ◽  
Small Area ◽  
Census Data ◽  
Housing Development ◽  
Age Group ◽  
Small Areas

The author describes a model for estimating and projecting the populations of communities living in small areas within cities. The model provides a means of updating the demographic inputs needed for projection between censuses and means of developing scenarios of demographic change and housing development. The method for estimating small-area populations between censuses is evaluated with recently published 1991 Census data. Single-year age-group detail is provided and the associated databases are embedded in a flexible user interface. Illustrative projections are discussed and interpreted for the northern English city of Bradford.

On the search for hosts and the egg distribution of some chalcid parasites of the knapweed gall-fly

Parasitology ◽  
1941 ◽  
Vol 33 (1) ◽  
pp. 47-66 ◽  
Author(s):  
G. C. Varley
Keyword(s):  
Small Area ◽  
Random Distribution ◽  
Random Search ◽  
Host Density ◽  
Oviposition Behaviour ◽  
Numerical Accuracy ◽  
Small Areas ◽  
Egg Distribution ◽  
First Approximation ◽  
Tentative Explanation

1. The egg distributions of five chalcid parasites of the knapweed gall-fly have been studied in a small area.2. A distinction is made between search for hosts by random movements, and random search in the sense of Nicholson; these terms are defined. Random movements may give rise to a distribution of parasitism different from that expected if search were purely random.3. The species discussed do not all distribute their eggs at random amongst the hosts. Some species superparasitize the hosts more, and one (Eurytoma curta) much less than would be expected if the egg distribution were purely random, owing to peculiarities in oviposition behaviour.4. Parasitism by E. curta is unevenly distributed in space, being higher in areas of high host density. This suggests that search is not exactly random, but is also concentrated in space. A tentative explanation is advanced based on the assumption that search is by random movements.5. Parasitism by E. robusta is very patchy. This non-random distribution is attributed to random movements performed by a very few parasites.6. It is concluded that these spatial discrepancies do not seriously affect the numerical accuracy of the assumption that search is random in small areas, and that the theory of Nicholson & Bailey may be accurate to a first approximation.

scholarly journals Comparison of three small-area mortality metrics according to urbanity in Korea: the standardized mortality ratio, comparative mortality figure, and life expectancy

2020 ◽  
Author(s):  
Ikhan Kim ◽  
Hwa-Kyung Lim ◽  
Hee-Yeon Kang ◽  
Young-Ho Khang
Keyword(s):  
Population Structure ◽  
Life Expectancy ◽  
Rural Areas ◽  
Small Area ◽  
Standardized Mortality Ratio ◽  
Small Areas ◽  
Mortality Figure ◽  
Specific Mortality ◽  
Small Area Level ◽  
Mortality Ratio

Abstract Background: This study aimed to compare three small-area level mortality metrics according to urbanity in Korea: the standardized mortality ratio (SMR), comparative mortality figure (CMF), and life expectancy (LE) by urbanity.Methods: We utilized the National Health Information Database to obtain annual small-area level age-specific numbers of population and deaths in Korea between 2013 and 2017. First, differences in the SMR by urbanity were examined, assuming the same age-specific mortality rates in all small-areas. Second, we explored the differences in ranking obtained using the three metrics (SMR, CMF, and LE). Third, the ratio of CMF to SMR by population was analyzed according to urbanity.Results: We found that the age-specific population distributions in urbanized areas were similar, but rural areas had a relatively old population structure. The age-specific mortality ratio also differed by urbanity. Assuming the same rate of age-specific mortality across all small-areas, we found that comparable median values in all areas. However, areas with a high SMR showed a strong predominance of metropolitan areas. The ranking by SMR differed markedly from the rankings by CMF and LE, especially in areas of high mortality, while the latter two metrics did not differ notably. The ratio of CMF to SMR showed larger variations in small-areas in rural areas, particularly in those with small populations, than in metropolitan and urban areas.Conclusions: In a comparison of multiple SMRs, bias could exist if the study areas have large differences in population structure. The use of CMF or LE should be considered for comparisons if it is possible to acquire age-specific mortality data for each small-area.

scholarly journals Spatiality in small area estimation: A new structure with a simulation study

2020 ◽  
Vol 15 (2) ◽  
Author(s):  
Yadollah Mehrabi ◽  
Amir Kavousi ◽  
Ahmad-Reza Baghestani ◽  
Mojtaba Soltani-Kermanshahi
Keyword(s):  
Spatial Correlation ◽  
Small Area ◽  
Small Area Estimation ◽  
Synthetic Data ◽  
Practical Applications ◽  
Small Areas ◽  
Area Estimation ◽  
Novel Structure ◽  
Specific Behaviour ◽  
Average Mean Square Error

In numerous practical applications, data from neighbouring small areas present spatial correlation. More recently, an extension of the Fay–Herriot model through the Simultaneously Auto- Rregressive (SAR) process has been considered. The Conditional Auto-Regressive (CAR) structure is also a popular choice. The reasons of using these structures are theoretical properties, computational advantages and relative ease of interpretation. However, the assumption of the non-singularity of matrix (Im-ρW) is a problem. We introduce here a novel structure of the covariance matrix when approaching spatiality in small area estimation (SAE) comparing that with the commonly used SAR process. As an example, we present synthetic data on grape production with spatial correlation for 274 municipalities in the region of Tuscany as base data simulating data at each area and comparing the results. The SAR process had the smallest Root Average Mean Square Error (RAMSE) for all conditions. The RAMSE also generally decreased with increasing sample size. In addition, the RAMSE valuess did not show a specific behaviour but only spatially correlation coefficient changes led to a stronger decrease of RAMSE values than the SAR model when our new structure was applied. The new approach presented here is more flexible than the SAR process without severe increasing RAMSE values.

Assessment of health and social security agency participants proportion using hierarchical bayesian small area estimation

2021 ◽  
Vol 16 (4) ◽  
pp. 241-250
Author(s):  
Ferra Yanuar ◽  
Atika Defita Sari ◽  
Dodi Devianto ◽  
Aidinil Zetra
Keyword(s):  
Social Security ◽  
Small Area ◽  
Small Area Estimation ◽  
Auxiliary Variable ◽  
Least Square ◽  
Hierarchical Bayesian ◽  
Strongly Correlated ◽  
Small Areas ◽  
Area Estimation ◽  
Owned Company

Data on the number of health insurance participants at the subdistrict level is crucial since it is strongly correlated with the availability of health service centers in the areas. This study’s primary purpose is to predict the proportion of health and social security participants of a state-owned company named Badan Penyelenggara Jaminan Sosial Kesehatan (BPJS) in eleven subdistricts in Padang, Indonesia. The direct, ordinary least square, and hierarchical Bayesian for small area estimation (HB-SAE) methods were employed in obtaining the best estimator for the BPJS participants in these small areas. This study found that the HB-SAE method resulted in better estimation than two other methods since it has the smallest standard deviation value. The auxiliary variable age (percentage of individuals more than 50 years old) and the percentage of health complaints have a significant effect on the proportion of the number of BPJS participants based on the HB-SAE method.

Comparison of EBLUP and EBLUP Modification in Estimating Small Areas (Study : Percentages of Poverty in Bogor District)

2018 ◽  
pp. 160-168
Author(s):  
Hary Merdeka ◽  
Kusman Sadik ◽  
Indahwati A
Keyword(s):  
Sample Size ◽  
Small Area ◽  
Small Sample Size ◽  
Large Error ◽  
Statistical Technique ◽  
Small Sample ◽  
Parameters Estimation ◽  
Small Areas ◽  
Modification Method ◽  
Size Estimates

A small area of the sample occurs when the sample size is very small. A large error will get if the parameters estimation is done with small the sample. One method to overcome it using a small area estimation (SAE) method. A small area estimator is a statistical technique to estimate the parameters of a sub-population with a small sample size. Estimates in the small area estimator method is based on the model and are indirect estimates. In this study the indirect method used is the EBLUP method and the modification of EBLUP estimator. The results of the alleged percentage of poverty in the Bogor district show that the EBLUP modification method is better compared to the expected method directly. This is based on the average of the RRMSE obtained.

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