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Published in 2022 at "Statistics in Medicine"
DOI: 10.1002/sim.9327
Abstract: Adaptive enrichment designs in clinical trials have been developed to enhance drug developments. They permit, at interim analyses during the trial, to select the sub‐populations that benefits the most from the treatment. Because of this…
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Keywords:
estimation;
time event;
selection;
estimator ... See more keywords
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Published in 2022 at "Statistics in Medicine"
DOI: 10.1002/sim.9512
Abstract: This article investigates a unified estimator for Cox regression model (Cox, 1972) when covariate data are missing at random (Rubin, 1976). It extends the idea of using parametric working models (Zhao and Liu, 2021) to…
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Keywords:
cox regression;
regression model;
cox;
unified estimator ... See more keywords
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Published in 2018 at "Circuits, Systems, and Signal Processing"
DOI: 10.1007/s00034-017-0548-z
Abstract: This paper focuses on the problem of fault detection (FD) for multi-agent networks when some follower agents are subjected to actuator or sensor faults. A distributed FD architecture is proposed by constructing a consensus-based estimator…
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Keywords:
fault detection;
estimator;
multi agent;
agent networks ... See more keywords
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Published in 2018 at "Circuits, Systems, and Signal Processing"
DOI: 10.1007/s00034-017-0587-5
Abstract: In the recent time, there have been investigation efforts into time domain channel estimation techniques, exploiting underlying sparseness in OFDM channel, for multiuser-based orthogonal frequency division multiplexing-interleave division multiple access (OFDM-IDMA) systems. This paper developed…
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Keywords:
estimator;
time;
channel estimation;
ofdm idma ... See more keywords
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Published in 2019 at "Empirical Economics"
DOI: 10.1007/s00181-019-01742-0
Abstract: New evidence in the literature on trade effects of the euro often reports different estimates. In this paper, I investigate the impact of trade data, instead of methodology, on the estimation of the key coefficient.…
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Keywords:
effects euro;
estimator;
trade effects;
ppml ... See more keywords
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Published in 2019 at "Metrika"
DOI: 10.1007/s00184-018-0703-y
Abstract: Auxiliary information is widely used in survey sampling to enhance the precision of estimators of finite population parameters, such as the finite population mean, percentiles, and distribution function. In the context of complex surveys, we…
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Keywords:
complex surveys;
auxiliary information;
estimator;
density ... See more keywords
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Published in 2019 at "Metrika"
DOI: 10.1007/s00184-019-00717-6
Abstract: In this paper, we propose a local linear estimator for the regression model $$Y=m(X)+\varepsilon $$Y=m(X)+ε based on the reciprocal inverse Gaussian kernel when the design variable is supported on $$(0,\infty )$$(0,∞). The conditional mean-squared error…
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Keywords:
regression;
inverse gaussian;
estimator;
local linear ... See more keywords
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Published in 2019 at "Metrika"
DOI: 10.1007/s00184-019-00751-4
Abstract: In the present note we consider general linear models where the covariates may be both random and non-random, and where the only restrictions on the error terms are that they are independent and have finite…
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Keywords:
parameter estimator;
estimator;
variance parameter;
general linear ... See more keywords
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Published in 2018 at "Statistical Papers"
DOI: 10.1007/s00362-016-0756-9
Abstract: Let h(.) be a continuous, strictly positive probability density function over an interval [a, b] and H(.) its associated cumulative distribution function (cdf). Given a sample set $$X_{1},\ldots ,X_{n}$$X1,…,Xn of independent identically distributed variables, we want…
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Keywords:
squared error;
mean;
estimator;
mean integrated ... See more keywords
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Published in 2019 at "Statistical Papers"
DOI: 10.1007/s00362-019-01090-2
Abstract: Consider two independent normal populations with a common variance and ordered means. For this model, we study the problem of estimating a common variance and a common precision with respect to a general class of…
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Keywords:
variance;
normal populations;
estimator;
estimating common ... See more keywords
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Published in 2019 at "Statistical Papers"
DOI: 10.1007/s00362-019-01141-8
Abstract: Consider a generalized random coefficient AR(1) model, $$y_t=\Phi _t y_{t-1}+u_t$$ , where $$\{(\Phi _t, u_t)^\prime , t\ge 1\}$$ is a sequences of i.i.d. random vectors, and a conditional self-weighted M-estimator of $$\textsf {E}\Phi _t$$ is…
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Keywords:
estimator;
self weighted;
weighted estimator;
asymptotics conditional ... See more keywords