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IJAR
2008
155views more  IJAR 2008»
13 years 8 months ago
Estimation of causal effects using linear non-Gaussian causal models with hidden variables
The task of estimating causal effects from non-experimental data is notoriously difficult and unreliable. Nevertheless, precisely such estimates are commonly required in many fiel...
Patrik O. Hoyer, Shohei Shimizu, Antti J. Kerminen...
ICC
2007
IEEE
119views Communications» more  ICC 2007»
14 years 2 months ago
On Channel State Inference and Prediction Using Observable Variables in 802.11b Network
—Performance of cross-layer protocols that recommend the relay of corrupted packets to higher layers can be improved significantly by accurately inferring/predicting the bit erro...
Shirish S. Karande, Syed A. Khayam, Yongju Cho, Ki...
IDA
2009
Springer
14 years 3 months ago
Ion-Selective Electrode Array Based on a Bayesian Nonlinear Source Separation Method
Ion-selective electrodes (ISE) offer a practical approach for estimating ionic activities. Nonetheless, such devices are not selective, i.e., the ISE response can be affected by ...
Leonardo Tomazeli Duarte, Christian Jutten, Sa&ium...
CORR
2008
Springer
69views Education» more  CORR 2008»
13 years 8 months ago
Information In The Non-Stationary Case
Information estimates such as the "direct method" of Strong et al. (1998) sidestep the difficult problem of estimating the joint distribution of response and stimulus by...
Vincent Q. Vu, Bin Yu, Robert E. Kass
CSDA
2010
194views more  CSDA 2010»
13 years 8 months ago
A clipped latent variable model for spatially correlated ordered categorical data
We propose a model for a point-referenced spatially correlated ordered categorical response and methodology for estimation of model parameters. Models and methods for spatially co...
Megan Dailey Higgs, Jennifer A. Hoeting