Pages that link to "Item:Q3057199"
From MaRDI portal
The following pages link to Discrete Time Rescaling Theorem: Determining Goodness of Fit for Discrete Time Statistical Models of Neural Spiking (Q3057199):
Displaying 14 items.
- The time-rescaling theorem and its application to neural spike train data analysis (Q122872) (← links)
- A common goodness-of-fit framework for neural population models using marked point process time-rescaling (Q1628363) (← links)
- Identification of sparse neural functional connectivity using penalized likelihood estimation and basis functions (Q1704742) (← links)
- Goodness-of-fit tests and nonparametric adaptive estimation for spike train analysis (Q2251601) (← links)
- Stability of point process spiking neuron models (Q2418230) (← links)
- Mapping of visual receptive fields by tomographic reconstruction (Q2840859) (← links)
- Applying the Multivariate Time-Rescaling Theorem to Neural Population Models (Q3016184) (← links)
- Binless Kernel Machine: Modeling Spike Train Transformation for Cognitive Neural Prostheses (Q3386405) (← links)
- Assessing Goodness-of-Fit in Marked-Point Process Models of Neural Population Coding via Time and Rate Rescaling (Q3386424) (← links)
- Parameter Estimation of Binned Hawkes Processes (Q5057223) (← links)
- Designing Patient-Specific Optimal Neurostimulation Patterns for Seizure Suppression (Q5157172) (← links)
- Nonlinear Modeling of Neural Interaction for Spike Prediction Using the Staged Point-Process Model (Q5157274) (← links)
- Likelihood Methods for Point Processes with Refractoriness (Q5378320) (← links)
- A biophysical and statistical modeling paradigm for connecting neural physiology and function (Q6172492) (← links)
