> I am estimating a system of seemingly unrelated regressions (SUR) in R. > Each of the equations has one unique regressor and one common regressor. I > am using `gmm::sysGmm` and am experimenting with different weighting > matrices. I get the same results (point estimates, standard erro...
For nonlinear analyses, VCDs were modeled using a spring element to simulate the connection stiffness in series with a generalized Maxwell model (GMM) which consists of one spring element in parallel with two Maxwell elements (spring and dashpot in series). The GMM is capable of simulating frequ...
R library(reticulate)dynpd<-import("pydynpd.regression",convert=TRUE)fd<-import("pandas",convert=TRUE)df<-fd$read_csv("data.csv")result<-dynpd$abond('n L(1:2).n w k | gmm(n, 2:4) gmm(w, 1:3) iv(k)',df, c('id','year')) ...
[59] 2018 UKF- GMMR Supervised Chiller (HVAC) Validate the feasibility of AGMM in chiller FDD. [47] 2018 Autoencoders Unsupervised Chiller (HVAC) Investigate the potential of autoencoders for detecting anomalies in building energy data. [60] 2018 DT, KNN Semi-supervised microgrid Investigate...
Using GMM estimation and elasticity testing of panel data for 423 firms from 12 emerging countries, we find that a country's safeguards tend to moderate the relationship between R&D and firm performance more than the system of a country. The results indicate that safeguarding is relatively more ...
The system GMM estimator developed by Blundell and Bond (1998) for dynamic panel data models has been widely used in empirical work; however, it does not perform well with weak instruments. This paper proposes a variation on the system GMM estimator, based on a simple transformation of the ...
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GMM background subtraction method demonstrates the background reduction by eliminating zeros in the pixels value [27]. For successful results, the background model is first rebuilt by averaging picture blocks, then the noise information is removed, and lastly, the background information is updated....
In subject area: Computer Science An iris recognition system is a biometric technology that involves acquiring, segmenting, normalizing, extracting features, and matching iris images to verify or identify individuals with high accuracy and security. ...
(2012a). Using a state-of-the-art HMM-based speech synthesiser, the FAR was shown to rise from 0.28% and 0% to 86% and 81% for the GMM-UBM and SVM systems respectively. This result is due to the significant overlap in the distribution of ASV scores for genuine and synthetic speech...