--- title: "model_parameters" authod: "Victor Navarro" output: rmarkdown::html_vignette bibliography: references.bib vignette: > %\VignetteIndexEntry{model_parameters} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- ```{r, include = FALSE, message = FALSE} library(calmr) ``` #### [RW1972](RW1972.html) ```{r} model_parameters("RW1972") ``` | Name | Symbol | Description | |:----|:----:|:---| |alphas|$\alpha$|Learning rate for presented stimulus| |betas_on, betas_off|$\beta_{on},\beta_{off}$|Intensity of presented and absent target| |lambdas|$\lambda$|Maximum learning supported by target| #### [MAC1975](MAC1975.html) ```{r} model_parameters("MAC1975") ``` | Name | Symbol | Description | |:----|:----:|:---| |alphas|$\alpha$|Starting associability (learning rate) for presented stimulus| |min_alphas, max_alphas|$\alpha_{min}, \alpha_{max}$|Minimum and maximum associability for stimulus| |betas_on, betas_off|$\beta_{on},\beta_{off}$|Intensity of presented and absent target| |lambdas|$\lambda$|Maximum learning supported by target| |thetas|$\theta$|Attentional learning rate parameter for stimulus| |gammas|$\gamma$|Attentional learning weight for stimulus| #### [PKH1982](PKH1982.html) ```{r} model_parameters("PKH1982") ``` | Name | Symbol | Description | |:----|:----:|:---| |alphas|$\alpha$|Learning rate for presented stimulus| |min_alphas, max_alphas|$\alpha_{min}, \alpha_{max}$|Minimum and maximum associability for stimulus| |betas_in, betas_ex|$\beta_{in},\beta_{ex}$|Learning rates for inhibitory and excitatory associations| |lambdas|$\lambda$|Maximum learning supported by target| |thetas|$\theta$|Decay/strengthening associability rate parameter for stimulus| |gammas|$\gamma$|Attentional learning weight for stimulus| #### [SM2007](SM2007.html) ```{r} model_parameters("SM2007") ``` | Name | Symbol | Description | |:----|:----:|:---| |alphas|$\alpha$|Learning rate for presented stimulus| |lambdas|$\lambda$|Maximum learning supported by target| |omegas|$\omega$|Weakening rate for presented stimulus| |rhos|$\rho$|Salience contribution for unconditioned activation of target| |gammas|$\gamma$|Contribution of stimulus to comparison process| |taus|$\tau$|Learning rate for operator switch| |order|$order$|Order for the comparison process| #### [HDI2020/HD2022](HD2022.html) ```{r} model_parameters("HDI2020") model_parameters("HD2022") ``` | Name | Symbol | Description | |:----|:----:|:---| |alphas|$\alpha$|Learning rate for presented stimulus| #### [TD](TD.html) ```{r} model_parameters("TD") ``` | Name | Symbol | Description | |:----|:----:|:---| |alphas|$\alpha$|Learning rate for presented stimulus| |betas_on, betas_off|$\beta_{on},\beta_{off}$|Intensity of presented and absent target| |lambdas|$\lambda$|Maximum learning supported by target| |gamma|$\gamma$|Temporal discount parameter| |sigma|$\sigma$|Rate of decay for eligibility traces| #### [ANCCR](ANCCR.html) ```{r} model_parameters("ANCCR") ``` | Name | Symbol | Description | |:----|:----:|:---| |reward_magnitude|$CW_{j,j}$|Reward magnitude for target| |betas|$\beta$|Unconditional value for target| |cost|$cost$|Response cost| |temperature|$temperature$|Temperature for softmax function| |threshold|$\theta$|Threshold to become meaningful causal target/putative cause| |k,alpha,alpha_reward|$k,\alpha,\alpha_{reward}$|Learning rates for predecessor representation, predecessor representation contingency, and causal weights. |w|$w$|Weight for net contingency computation| |minimum_rate|$minimum\_rate$|Lower bound on perceivable event rates| |sampling_interval|$sampling\_interval$|Time interval to update base rate calculations| |use_exact_mean|$use\_exact\_mean$|Whether to use exact mean calculations for $\alpha$| |t_ratio|$t\_ratio$|Ratio to calculate time constant| |use_timed_alpha|$use\_timed\_alpha$|Whether to use exponential decay for $\alpha$| |alpha_exponent, alpha_init, alpha_min|$alpha\_exponent,alpha\_init, alpha\_min$|Parameters for exponential decay of $\alpha$| |add_beta|$add\_beta$|Whether to add $\beta$ to dopaminergic activity| |jitter|$jitter$|Magnitude of perceptual noise for simultaneous events| #### [RAND](RAND.html) ```{r} model_parameters("RAND") ``` | Name | Symbol | Description | |:----|:----:|:---| |alphas|$\alpha$|Placeholder; no meaning.|