Estimation Of Different Types Research Articles

On improved class of difference type estimators for population median in survey sampling

We propose two new improved class of difference type estimators for population median under simple random sampling (SRS) and two-phase sampling (TPS). Expressions for bias and MSE are derived up to first order of approximation. We make a comparison of proposed estimators with all other commonly known estimators in literature. Numerical findings show that the proposed class of estimators perform better as compared to all other estimators considered here.

A modified efficient difference-type estimator for population mean under two-phase sampling design

A modified efficient difference-type estimator for population mean under two-phase sampling design

An Improved Regression Type Estimator of Population Mean with Two Auxiliary Variables in Stratified Double Sampling

Shabbir (Commun Stat Theory Methods 47(1):92–101, 2018) suggested a new difference type estimator of finite population mean in stratified double sampling using the ranks of two auxiliary variables as additional information. In this paper, on applying Searls’s (J Am Stat Assoc 59:1225–1226, 1964) approach to Shabbir’s (2018) estimator, we propose an improved estimator of population mean. The expressions of bias and mean square error of the proposed estimator have been obtained, up to first order of approximation. Theoretical and numerical comparisons of the mean square error of the proposed estimator with that of various existing estimators have been made. It is observed that proposed estimator always performs better than Shabbir’s (2018) estimator and also better than most of the other various existing estimators in the literature of survey sampling.

A new improved difference-cum-exponential ratio type estimator in systematic sampling two auxiliary variables

A difference-cum-exponential ratio type estimator was proposed for estimating the finite population mean using two auxiliary variables under systematic sampling. Expressions for the biases and mean square errors (MSEs) were derived up to first order of approximation. It was observed that the proposed estimator is more efficient than the usual sample mean estimator, traditional ratio estimator, exponential-ratio estimator and many other recently proposed difference type estimators in terms of MSEs. Four datasets were used for efficiency comparisons.

Defect size estimation method for magnetic flux leakage signals using convolutional neural networks

A method for defect size estimation of magnetic flux leakage (MFL) signals using convolutional neural networks (CNNs) is proposed to overcome the problem of quantitative identification of pipeline MFL testing. The model mainly includes two modules: defect classification and defect size regression. The former is used to realise data fusion, feature extraction and tasks of three components (axial, circumferential and radial) of the MFL defect signal. The defect size regression module includes seven CNNs, which realise the size estimation of different types of defect. The input is a different type of defect in the defect classification module and the output is the length, width and depth information of the defect. Finally, the training and prediction are conducted using a defect dataset. The results show that the proposed method can effectively identify the MFL defect size of the pipeline.

DNA detection of a temporary and original user of an office space

There is a need to improve our awareness of the transfer, persistence, prevalence and recovery of DNA (DNA-TPPR) from items/surfaces, and within different spaces and circumstances, to assist sample targeting during collection and activity level assessments. Here we investigate DNA-TPPR within office spaces. Specifically, to what extent DNA, left by a temporary user of an office space that has been occupied by a regular user for an extended period, is detectable when the duration of their temporary occupancy and their general activities are known. Also, how readily the DNA of the regular user is still detectable after a known period of occupancy by another person, and to what extent DNA of others is present.Samples were collected from 18 core items/surfaces within eight single use office spaces that had been used temporarily by another occupant for 2.5–7 h. Four of these offices were within one forensic laboratory and four within another. Each lab collected and processed the samples to generate DNA profiles using their own set of methodologies.The owner/regular user of an office space was found to be the major/majority contributor to profiles from most items within the space, even after temporary use by another person. The detectability of the temporary occupier of an office space varied among offices and items. The temporary occupier was not observed on all items touched. In most instances, when detected, the temporary occupier was known to have touched the surface at some stage. Therefore, where one is seeking to collect samples that may detect a temporary user of a space, it is advisable to target several potentially touched sites.A difference in methodologies applied from collection through to profiling appears to impact DNA yields and profile types. Ascertaining the impact of using different methodologies on the profiles generated from collected samples, requires further research. More research is also needed to generate data to help determine frequency estimates for different types of profiles given different user histories of an item or space.

Access to Internet-based mental health resources in a nationally representative sample of Canadian active duty military personnel

Introduction: The Canadian Armed Forces (CAF) have made access to mental health care a priority. Access to care is typically conceptualized as in-person interactions with health care providers; however, it can also include virtual health care services. Virtual health care is health services delivered through an Internet platform. Internet-based interventions are promising for increasing mental health care access among CAF personnel; however, increased reliance on Internet technology for service provision may create disparate access. Accordingly, a recent nationally representative sample of CAF Regular Forces personnel was examined with the following aims: (1) provide estimates of different types of Internet use for mental health-related problems and contrast such estimates with usage rates for other forms of professional and paraprofessional care; (2) examine the relationship between Internet use for mental health-related problems, professional mental health service use, and perceived need for care; and (3) identify individual predictors of Internet use for mental health-related problems. Methods: Prevalence estimates were computed for all variables of interest and multivariate logistic regression analyses served to identify predictors of Internet use. Results: The results indicate that the Internet is more readily accessed for mental health care than other forms of paraprofessional services but remains less commonly accessed than in-person mental health care providers. Results also indicate that the Internet is primarily used to obtain information about symptoms or where to get help. Discussion: Findings suggest few individual barriers exist for accessing the Internet and Internet-based technologies may be a viable alternative for increasing access to mental health resources among CAF personnel and their families.

Composite quantile regression estimation of linear error-in-variable models using instrumental variables

In this paper, we develop a composite quantile regression estimator of linear error-in-variable models based on instrumental variables. The proposed estimator is consistent and asymptotically normal under fairly general assumptions. It neither requires the measurement errors and the regression errors to have the same variance nor to belong to the same location-scale symmetric distribution. The simulation results show that the proposed method generates unbiased and efficient estimates for different types of the distributions of the regression errors in finite samples. An application to real data collected from the survey of identical twins to study the economic returns to schooling is also provided.

Improved class of difference-type estimators for population median in survey sampling

The improved classes of difference-type estimators of finite population median by using auxiliary information in simple random sampling and two-phase sampling have been proposed. The expressions for bias and mean square error are derived up to first order of approximation. Efficiency conditions and numerical comparisons reveal that the proposed class of estimators performs better than the other estimators under same scenario. Using fixed cost the optimum values are obtained for the two-phase sampling scheme.

Trade‐offs on fault estimation via proportional multiple‐integral and multiple‐resonant observers for discrete‐time systems

The authors develop a fault estimation strategy which is based on a novel proportional multiple-integral (PMI) and multiple-resonant observer. This observer is an extension of the well-known PMI observer and it is able to estimate from low to high-frequency fault signals. The proposed estimation strategy is applied to discrete-time systems which are affected by faults and stochastic noises. We present a multi-objective design strategy of the observer that fixes the trade-offs between practical engineering parameters regarding the noise attenuation and the ability to track each kind of fault dynamics considered by the augmented observer. They study the influence of the order of the observer on the steady-state and transient performance of the estimation of different types of faults. Finally, a numerical example is given to illustrate the effectiveness of the proposed observer, design and characterisation.

Estimating the Returns to Public R&D Investments: Evidence from Production Function Models

This paper analyses the returns to publicly performed R&D investments in 22 OECD countries. We exploit a dataset containing time-series from 1963 to 2011 and compare the estimates of different types of production function models. Robustness analyses are performed to test the sensitivity of the outcomes for particular specifications, sample selections, assumptions about the construction of R&D stocks, and variable definitions. Analyses based on Cobb–Douglas and translog production functions mostly yield statistically insignificant or negative returns. In these models we control for private and foreign R&D investments and the primary production factors. Models including additional controls, such as public capital, the stock of inward and outward foreign direct investment, and the shares of high-tech imports and exports, yield more positive returns. Our findings suggest that publicly performed R&D investments do not automatically foster GDP and TFP growth in production function models. Furthermore, our estimates suggest that economic returns to publicly performed R&D seem to depend on the specific national context.

Characteristics of Intimate Partner Violence in China: Gender Symmetry, Mutuality, and Associated Factors.

The primary research focus on female victims of intimate partner violence (IPV), coupled with a lack of discussion on mutual violence between intimate partners, has affected our understanding of IPV in China. In the current study, we aim to examine gender symmetry and mutuality in IPV in China. We also produce the first age-specific and gender-specific prevalence estimates for different types of IPV. The associations between IPV, demographic factors, personal factors, and relationship factors are also examined. We analyzed a set of data from 7,466 households in six regions in China collected between 2009 and 2010. Three-way cross-tab analyses and multinomial logistic regressions were performed to examine the prevalence of IPV in the preceding year by gender and age groups and its associations with different individual and relationship factors, respectively. For sexual violence and severe physical assault and injury, most victims experienced unidirectional violence. For psychological aggression and minor physical assault, mutual violence was more likely to occur among intimate partners. Gender symmetry was found in regard to physical assault and psychological aggression. There is gender asymmetry in sexual violence between Chinese intimate partners. Older individuals are less likely to be victims or perpetrators of IPV or to be involved in mutual violence. Factors associated with IPV show that mutual violence is generally analogous to violence perpetration. To prevent IPV, it is important to understand gender symmetry and mutuality of IPV in China. We need to involve both men and women in violence prevention and develop age-appropriate programs in the future.

Assessing the performance of near real-time rainfall products to represent spatiotemporal characteristics of extreme events: case study of a subtropical catchment in south-eastern Brazil

ABSTRACTThis study evaluates the performance of four Near Real-Time (NRT) satellite rainfall products in estimating the spatiotemporal characteristics of different extreme rainfall events in a subtropical catchment in south-eastern Brazil. The Climate Prediction Centre Morphing algorithm (CMORPH), Tropical Rainfall Measuring Mission, Multisatellite Precipitation Analysis in real time (TMPA-RT), the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Global Cloud Classification System (PERSIANN-GCCS), and the Hydro-Estimator are evaluated for monsoon seasons, based on their capability to represent four types of rainfall events distinguished for: (1) local and short duration, (2) long-lasting event, (3) short and spatial extent, and (4) spatial extent and long lasting. Since the events are defined relative to a percentile, the relative performance variation at different threshold levels (75th, 90th, and 95th) is also evaluated. The data from the 13 Automatic Weather Stations (AWSs) for the period from 2007 to 2014 are used as the reference. The results show that the product performance highly depends on the spatiotemporal characteristics of rainfall events. All four products tend to overestimate intense rainfall in the study area, especially in high altitude zones. CMORPH had the best overall performance to estimate different types of extreme spatiotemporal events. The results allow for developing a better understanding of the accuracy of the NRT products for the estimation of different types of rainfall events.

The possibility of shrinkage strain reduction in cements mortars

The subject of the paper is presentation of action mechanism and effectiveness estimation of different types of chemical admixtures that make it possible to control the course of shrinkage strains associated with cement hydration process. There are presented tests results from the research program realization in which there were used the basic types of admixtures allowing for producing mortars and concretes with reduced or compensated shrinkage. In conducted tests there were applied admixtures based on calcium oxide, multi-molecule alcohol as well as water polymer dispersions (styrene-acrylic co-polymer - SA and styrene-butadiene latex - SBR). Their influence onto the magnitude of shrinkage strain and strength development for cement mortars was analyzed.

Avaliação do albedo nos diferentes tipos de cobertura do cerrado do Amapá - Brasil com imagens MODIS

O presente estudo visa fazer um estudo comparativo da estimativa do albedo em diferentes alvos em áreas no Amapá. O albedo determina o poder refletor da superfície no domínio espectro do sol e, é um dos componentes fundamental na estimativa do balanço de radiação da superfície. Utilizaram-se três imagens do sensor MODIS /Terra para os anos de 2002, 2006 e 2012. O processamento da das imagens foi feita pelo programa ERDAS. Empregaram algoritmos os de Liang e Tasumi para estimar o albedo nas áreas composto por área urbana, cerrado e floresta nativa e silvicultura de eucaliptos. Os resultados obtidos pelos dois métodos são eficazes na estimativa do albedo. A relação entre os valores médios estimados pelos métodos apresentou uma correlação de r=0,88 erro percentual médio EPM = 7,8% e erro padrão médio EPAM = 0,012 para o nível de significância α.

Intercomparison of Ocean Color Algorithms for Picophytoplankton Carbon in the Ocean

The differences among phytoplankton carbon ($C_{phy}$) predictions from six ocean colour algorithms are investigated by comparison with \textit{in situ} estimates of phytoplankton carbon. The common satellite data used as input for the algorithms is the Ocean Colour Climate Change Initiative merged product. The matching \textit{in situ} data are derived from flow cytometric cell counts and per-cell carbon estimates for different types of pico-phytoplankton. This combination of satellite and \textit{in situ} data provides a relatively large matching dataset (N$>$500), which is independent from most of the algorithms tested and spans almost two orders of magnitude in $C_{phy}$. Results show that not a single algorithm outperforms any of the other when using all matching data. Concentrating on the oligotrophic regions ($B$ \textless 0.15 mg\,Chl\,m$^{-3}$), where flow cytometric analysis captures most of the phytoplankton biomass, reveals significant differences in algorithm performance. The bias ranges from -35\% to +150\% and RMSD (unbiased) from 5 to 10 mg\,C\,m$^{-3}$ among algorithms, with chlorophyll-based algorithms performing better than the rest. The backscattering-based algorithms produce different reasults at the clearest waters and these differences are discussed in terms of the different algorithms used for $b_{bp}$ retrieval.

A New Estimator of Mean Using Double Sampling

Abstract In this paper, we consider the problem of estimation of population mean of a study variable by making use of first-phase sample mean and first-phase sample median of the auxiliary variable at the estimation stage. The proposed new estimator of the population mean is compared to the sample mean estimator, ratio estimator and the difference type estimator for the fixed cost of the survey by using the concept of two-phase sampling. The magnitude of the relative efficiency of the proposed new estimator has been investigated through simulation study.

Efficient utilization of two auxiliary variables in stratified double sampling

ABSTRACTIn this article, we propose a new difference-type estimator in estimating the finite population mean in stratified double sampling by using the ranks of two auxiliary variables as an additional information. The proposed estimator performs better than the usual sample mean estimator, ratio estimator, exponential estimator, Choudhury and Singh (2012) estimator, Vishwakarma and Gangele (2014) estimator, Singh and Khalid (2015) estimator, Khan and Al-Hossain (2016) estimator, Khan (2016) estimator, and the usual difference estimator. Two real datasets are used to observe the performances of estimators.

CONCEPTION OF LEVEL OF SERVICE OF PUBLIC INTERMODAL TRANSPORT JUNCTIONS

The planning of passenger intermodal transport nodes consider like an important part of sustainable transportation system. For projecting of passenger transport junction give consideration in the current urban planning. This article shows the concept of the level of service for functional estimation of different types of transport infrastructure and network of streets. Supposition was made by author about the main indicator of service level of intermodal nodes functional which is used to estimate the transport junction. Author suggests to estimate the level of service of users of intermodal passenger using indicator of total cost of time required to transfer, which are a sum of costs of time required to move from landing to boarding area and time of transport expectation. It is offered to set the boarders of level of service on the basis of inverse distribution indicators of the whole duration of interchanging that was determined using results of researching of different types of intermodal passenger nodes. The development of evaluation scale of levels of service will be performed on the basis of data that were got during the researching of transfer hubs in Vienna. In the future the approbation of this scale using the example of function quality evaluation number of passenger transport nodes of Irkutsk and Moscow and following development of practical recommendation.

Estimation of finite population mean in simple and stratified random sampling using two auxiliary variables

ABSTRACTWe propose an improved difference-cum-exponential ratio type estimator for estimating the finite population mean in simple and stratified random sampling using two auxiliary variables. We obtain properties of the estimators up to first order of approximation. The proposed class of estimators is found to be more efficient than the usual sample mean estimator, ratio estimator, exponential ratio type estimator, usual two difference type estimators, Rao (1991) estimator, Gupta and Shabbir (2008) estimator, and Grover and Kaur (2011) estimator. We use six real data sets in simple random sampling and two in stratified sampling for numerical comparisons.