書(shū)目名稱(chēng)Biased Sampling, Over-identified Parameter Problems and Beyond影響因子(影響力)學(xué)科排名
書(shū)目名稱(chēng)Biased Sampling, Over-identified Parameter Problems and Beyond網(wǎng)絡(luò)公開(kāi)度
書(shū)目名稱(chēng)Biased Sampling, Over-identified Parameter Problems and Beyond網(wǎng)絡(luò)公開(kāi)度學(xué)科排名
書(shū)目名稱(chēng)Biased Sampling, Over-identified Parameter Problems and Beyond被引頻次
書(shū)目名稱(chēng)Biased Sampling, Over-identified Parameter Problems and Beyond被引頻次學(xué)科排名
書(shū)目名稱(chēng)Biased Sampling, Over-identified Parameter Problems and Beyond年度引用
書(shū)目名稱(chēng)Biased Sampling, Over-identified Parameter Problems and Beyond年度引用學(xué)科排名
書(shū)目名稱(chēng)Biased Sampling, Over-identified Parameter Problems and Beyond讀者反饋
書(shū)目名稱(chēng)Biased Sampling, Over-identified Parameter Problems and Beyond讀者反饋學(xué)科排名
作者: 哀求 時(shí)間: 2025-3-21 21:05
Causal Inference and Missing Data Problems,ental problem of causal inference is that we can only observe one of the two potential outcomes for a particular subject. It is impossible to conduct a paired t-test for the assessment of treatment effects. On the other hand, the unpaired two sample t-test or Wilcoxon test may produce biased results作者: convulsion 時(shí)間: 2025-3-22 03:06
Bildung und virtuelle Welten - Cyberbildungental problem of causal inference is that we can only observe one of the two potential outcomes for a particular subject. It is impossible to conduct a paired t-test for the assessment of treatment effects. On the other hand, the unpaired two sample t-test or Wilcoxon test may produce biased results作者: 半球 時(shí)間: 2025-3-22 07:15 作者: 裝入膠囊 時(shí)間: 2025-3-22 09:34
Book 2017 problems. Biased sampling problems appear in many areas of research, including Medicine, Epidemiology and Public Health, the Social Sciences and Economics. The book addresses a range of important topics, including case and control studies, causal inference, missing data problems, meta-analysis, ren作者: FEMUR 時(shí)間: 2025-3-22 13:06
2199-0980 sively discusses many different biased sampling problems.ExpThis book is devoted to biased sampling problems (also called choice-based sampling in Econometrics parlance) and over-identified parameter estimation problems. Biased sampling problems appear in many areas of research, including Medicine, 作者: Exaggerate 時(shí)間: 2025-3-22 20:15 作者: convert 時(shí)間: 2025-3-23 01:07 作者: Comprise 時(shí)間: 2025-3-23 05:00
Advances in Intelligent and Soft Computingi.d. representation of a noncentral hypergeometric distribution as the summation of independent Bernoulli trials with possible different success probabilities. As a consequence, it will be very easy to conduct statistical inferences and to derive the Central Limit Theorem for a series of . tables.作者: hypertension 時(shí)間: 2025-3-23 06:04
Brief Introduction of Renewal Process, until next bus arrives. The next bus could arrive immediately, or one could be unlucky with time . just after the previous bus left and could wait as long as 20 minutes for the next bus. Interestingly this waiting time is no longer uniformly distributed. This is the so-called “inspection paradox”.作者: 向外供接觸 時(shí)間: 2025-3-23 11:09
Heuristical Introduction of General Biased Sampling with Various Applications,representing the target population. This problem appears naturally in evidence based economic, epidemiological, and medical research in which observational studies are conducted. We call this type of biased sampling “natural selection biased sampling problems”.作者: Expertise 時(shí)間: 2025-3-23 14:47
Noncentral Hypergeometric Distribution and Poisson Binomial Distribution,i.d. representation of a noncentral hypergeometric distribution as the summation of independent Bernoulli trials with possible different success probabilities. As a consequence, it will be very easy to conduct statistical inferences and to derive the Central Limit Theorem for a series of . tables.作者: Generic-Drug 時(shí)間: 2025-3-23 19:30
Book 2017.The goal of this book is to make it easier for Ph. D students and new researchers to get started in this research area. It will be of interest to all those who work in the health, biological, social and physical sciences, as well as those who are interested in survey methodology and other areas of statistical science, among others.?.作者: insightful 時(shí)間: 2025-3-24 00:46 作者: Malleable 時(shí)間: 2025-3-24 05:46
Brief Introduction of Renewal Process,minutes, where . is uniformly distributed between 10 and 20. It is natural to wonder how long one is expected to wait from some random point in time . until next bus arrives. The next bus could arrive immediately, or one could be unlucky with time . just after the previous bus left and could wait as作者: 聽(tīng)寫(xiě) 時(shí)間: 2025-3-24 07:15 作者: analogous 時(shí)間: 2025-3-24 13:06 作者: cardiopulmonary 時(shí)間: 2025-3-24 17:13 作者: 在駕駛 時(shí)間: 2025-3-24 21:21
Noncentral Hypergeometric Distribution and Poisson Binomial Distribution, researches, a series of . tables have been used extensively. Next we present a fundamental result by Kou and Yin (Stat Sin 809–829:8, 1996) on the i.i.d. representation of a noncentral hypergeometric distribution as the summation of independent Bernoulli trials with possible different success proba作者: Defense 時(shí)間: 2025-3-25 00:14 作者: 預(yù)示 時(shí)間: 2025-3-25 05:45 作者: 出血 時(shí)間: 2025-3-25 10:18 作者: 心胸開(kāi)闊 時(shí)間: 2025-3-25 15:02 作者: neutral-posture 時(shí)間: 2025-3-25 16:17 作者: N斯巴達(dá)人 時(shí)間: 2025-3-25 22:28 作者: 弓箭 時(shí)間: 2025-3-26 04:00 作者: ALLAY 時(shí)間: 2025-3-26 06:14
Ewaryst Tkacz,Adrian Kapczynskiheme that depends on the outcome. In an outcome dependent sampling, the tails of a distribution are over-sampled to compensate for the low probability of making observation in the tails under a random sampling.作者: Processes 時(shí)間: 2025-3-26 08:34 作者: optional 時(shí)間: 2025-3-26 12:43 作者: colloquial 時(shí)間: 2025-3-26 18:28 作者: 使迷惑 時(shí)間: 2025-3-26 23:07
Generalized Method of Moments,ound-break work, Hansen was awarded Nobel prize in 2013. The generalized method of moments (henceforth GMM) has become an important unifying framework for inference in econometrics during the last thirty years.作者: photophobia 時(shí)間: 2025-3-27 01:43 作者: 變形 時(shí)間: 2025-3-27 07:23
https://doi.org/10.1007/978-981-10-4856-2Biased Sampling Problems; Finite Mixture Models; Genetic Epidemiology; Parametric Likelihood; Survey Sam作者: KEGEL 時(shí)間: 2025-3-27 09:37
978-981-13-5249-2Springer Nature Singapore Pte Ltd. 2017作者: Cytokines 時(shí)間: 2025-3-27 16:17 作者: 混雜人 時(shí)間: 2025-3-27 18:40
Alexander S. Sinyukin,Boris G. Konoplevnaturally collects samples from a population, but the sampling distribution is different from the target population. It happens because not every unit in the population has an equal chance to be sampled when the natural sampling plan is adopted.作者: 一個(gè)攪動(dòng)不安 時(shí)間: 2025-3-27 22:33
https://doi.org/10.1007/978-3-658-43992-7ound-break work, Hansen was awarded Nobel prize in 2013. The generalized method of moments (henceforth GMM) has become an important unifying framework for inference in econometrics during the last thirty years.作者: 信徒 時(shí)間: 2025-3-28 03:53 作者: ALIEN 時(shí)間: 2025-3-28 09:18 作者: 我邪惡 時(shí)間: 2025-3-28 13:34
https://doi.org/10.1007/978-3-658-31493-4Classical statistical inference emphasizes unbiased estimators rather than unbiased estimating equations.作者: acetylcholine 時(shí)間: 2025-3-28 16:27
https://doi.org/10.1007/978-3-658-31493-4The projection method can be used not only in finitely many parameter problems but also in nuisance function or infinite many nuisance parameters cases.作者: 確定 時(shí)間: 2025-3-28 20:18
Schlussfolgerung und Diskussion,The maximum likelihood method for regular parametric models has many optimality properties. As a result, it is one of the most popular methods in statistical inference. However, model mis-specification is a big concern since a misspecified model may lead to bias results.作者: squander 時(shí)間: 2025-3-28 23:52
https://doi.org/10.1007/978-3-642-11710-7Besides empirical likelihood, the Kullback–Leibler likelihood is another popular method to calibrate auxiliary information. The entropy family has also been used extensively in information theory. We mainly focus on discussions for continuous random variable cases. The discrete cases can be treated similarly.作者: 調(diào)味品 時(shí)間: 2025-3-29 06:44 作者: 良心 時(shí)間: 2025-3-29 09:48 作者: 套索 時(shí)間: 2025-3-29 13:52
https://doi.org/10.1007/978-3-322-95257-8In this chapter we study conditional likelihood-based inference in discrete outcome problems. This method is very useful for sparse data where there exists a large number of nuisance parameters. Moreover it is used extensively in matched case-control studies where some baseline covariates or survival times are matched at the data collection stage.作者: Antimicrobial 時(shí)間: 2025-3-29 16:15 作者: acrobat 時(shí)間: 2025-3-29 22:03 作者: 閑逛 時(shí)間: 2025-3-30 00:13 作者: Hyperplasia 時(shí)間: 2025-3-30 06:32
Internet - Bildung - GemeinschaftIn this Chapter we present the results by Qin and Zhang (Biometrika 92:251–270, 2005) and Li and Qin (JASA 496:1476–1484, 2011) on the connection between marginal likelihood, conditional likelihood and empirical likelihood.作者: 啜泣 時(shí)間: 2025-3-30 09:23
Brief Review of Parametric Likelihood Inferences,Maximum likelihood estimation (MLE) under regular conditions can be found in most statistical books. In non-regular cases, however, it involves all kinds of problems, such as solution on the boundary of parameter space, multiple roots, non-existence, inconsistency in the presence of many incidental parameters, etc.作者: incarcerate 時(shí)間: 2025-3-30 13:39 作者: abduction 時(shí)間: 2025-3-30 17:04 作者: Desert 時(shí)間: 2025-3-30 21:09
Empirical Likelihood with Applications,The maximum likelihood method for regular parametric models has many optimality properties. As a result, it is one of the most popular methods in statistical inference. However, model mis-specification is a big concern since a misspecified model may lead to bias results.作者: 解脫 時(shí)間: 2025-3-31 01:56
,Kullback–Leibler Likelihood and Entropy Family,Besides empirical likelihood, the Kullback–Leibler likelihood is another popular method to calibrate auxiliary information. The entropy family has also been used extensively in information theory. We mainly focus on discussions for continuous random variable cases. The discrete cases can be treated similarly.作者: GREG 時(shí)間: 2025-3-31 09:03 作者: LURE 時(shí)間: 2025-3-31 12:11 作者: 蕨類(lèi) 時(shí)間: 2025-3-31 16:58 作者: 領(lǐng)袖氣質(zhì) 時(shí)間: 2025-3-31 20:22
Discrete Data Models,The logistic regression model has been widely used in statistical literature for analyzing categorical data. In this chapter we present many other useful discrete data models. If the data collection process is retrospective, then we end up with different biased sampling problems.作者: Obstruction 時(shí)間: 2025-4-1 00:10 作者: CUMB 時(shí)間: 2025-4-1 03:59
Inferences and Tests in Semiparametric Finite Mixture Models,Mixture models have been widely used in many disciplines, including econometric, psychosocial, genetic and medical researches and many others.作者: FUSC 時(shí)間: 2025-4-1 09:46
