# Metropolis-Hastings Algorithm for Bayesian Hierarchical model

I have developed a Metropolis-Hastings Algorithm for a double sigmoidal model, but now the aim is to create a Bayesian Hierarchical model that depends on incoming temperature data. For example, the asymptote parameter will be written as:

$$\alpha_{0t} = \alpha_{0} + T*u_{t},$$ $$\alpha_{0} \sim N(90,10),$$ $$u_{t} \sim N(0, \sigma^2)$$

where T is the temperature data. The current sampler for this variable is as follows, with all the other relevant variables included in the loglikelihood functions:

a0n <- rnorm(1,a0,0.025)