Time-varying models in econometrics: Identifiability and estimation

2006 ◽  
pp. 612-625 ◽  
Author(s):  
Kent D. Wall
Keyword(s):  
Time Varying ◽  
Time Varying Models

scholarly journals Simultaneous inference for time-varying models

2021 ◽  
Author(s):  
Sayar Karmakar ◽  
Stefan Richter ◽  
Wei Biao Wu
Keyword(s):  
Simultaneous Inference ◽  
Time Varying ◽  
Time Varying Models

scholarly journals Using time-varying models to estimate post-transplant survival in pediatric liver transplant recipients

PLoS ONE ◽  
2018 ◽  
Vol 13 (5) ◽  
pp. e0198132 ◽  
Author(s):  
Cindy L. Bryce ◽  
Chung Chou H. Chang ◽  
Yi Ren ◽  
Jonathan Yabes ◽  
Gabriel Zenarosa ◽  
...  
Keyword(s):  
Liver Transplant ◽  
Time Varying ◽  
Transplant Recipients ◽  
Transplant Survival ◽  
Post Transplant ◽  
Pediatric Liver ◽  
Liver Transplant Recipients ◽  
Time Varying Models ◽  
Pediatric Liver Transplant

scholarly journals Identification Theory for Time Varying Models

10.3386/w0127 ◽  
1976 ◽  
Author(s):  
Thomas Cooley ◽  
Kent Wall
Keyword(s):  
Time Varying ◽  
Identification Theory ◽  
Time Varying Models

scholarly journals Recursive online IV method for identification of continuous-time slowly time-varying models in closed loop

2017 ◽  
Vol 50 (1) ◽  
pp. 4008-4013 ◽  
Author(s):  
A. Padilla ◽  
H. Garnier ◽  
P.C. Young ◽  
J. Yuz
Keyword(s):  
Continuous Time ◽  
Closed Loop ◽  
Time Varying ◽  
Time Varying Models

scholarly journals A need for time-varying models to suppress artefacts of tACS in the M/EEG

2021 ◽  
Author(s):  
Nicholas S Bland
Keyword(s):  
False Positive ◽  
Brain Activity ◽  
Neural Oscillations ◽  
Time Varying ◽  
Positive Evidence ◽  
Specific Manner ◽  
Transcranial Alternating Current Stimulation ◽  
Time Invariance ◽  
Eeg Recordings ◽  
Time Varying Models

Rhythmic modulation of brain activity by transcranial alternating current stimulation (tACS) can entrain neural oscillations in a frequency- and phase-specific manner. However, large stimulation artefacts contaminate concurrent 'online' neuroimaging measures, including magneto- and electro-encephalography (M/EEG) — restricting most analyses to periods free from stimulation ('offline' aftereffects). While many published methods exist for removing artefacts of tACS from M/EEG recordings, they universally assume linear artefacts: either time-invariance (i.e., an artefact is a scaled version of itself from cycle to cycle) or sensor-invariance (i.e., artefacts are scaled versions of one another from sensor to sensor). However, heartbeat and respiration both nonlinearly modulate the amplitude and phase of these artefacts, predominantly via changes in scalp impedance. The spectral symmetry this introduces to the M/EEG spectra may lead to false-positive evidence for entrainment around the frequency of tACS, if not adequately suppressed. Good electrophysiological evidence for entrainment therefore requires that tACS artefacts are fully accounted for before comparing online spectra to a control (e.g., as might be observed during sham stimulation). Here I outline an approach to linearly solve templates for tACS artefacts, and demonstrate how event-locked perturbations to amplitude and phase can be introduced from simultaneous recordings of heartbeat and respiration — effectively forming time-varying models of tACS artefacts. These models are constructed for individual sensors, and can therefore be used in contexts with few EEG sensors and with no assumption of artefact collinearity. I also discuss the feasibility of this approach in the absence of simultaneous recordings of heartbeat and respiration traces.

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