add.local.level: Local level trend state component
In michelletran/bsts: Bayesian Structural Time Series

Add a local level model to a state specification. The local level model assumes the trend is a random walk:

alpha[t+1] = alpha[t] + rnorm(1, 0, sigma).

The prior is on the sigma parameter.

  AddLocalLevel(
     state.specification,
     y,
     sigma.prior,
     initial.state.prior,
     sdy,
     initial.y)

`state.specification`	A list of state components that you wish to add to. If omitted, an empty list will be assumed.
`y`	The time series to be modeled, as a numeric vector.
`sigma.prior`	An object created by `SdPrior` describing the prior distribution for the standard deviation of the random walk increments.
`initial.state.prior`	An object created using `NormalPrior`, describing the prior distribution of the initial state vector (at time 1).
`sdy`	The standard deviation of the series to be modeled. This will be ignored if `y` is provided, or if all the required prior distributions are supplied directly.
`initial.y`	The initial value of the series being modeled. This will be ignored if `y` is provided, or if the priors for the initial state are all provided directly.