more docstrings

src/get_functions.jl

@@ -1479,7 +1479,9 @@ ss(args...; kwargs...) = get_steady_state(args...; kwargs...)
 
 """
 $(SIGNATURES)
-Return the solution of the model. In the linear case it returns the linearised solution and the non stochastic steady state (SS) of the model. In the nonlinear case (higher order perturbation) the function returns a multidimensional array with the endogenous variables as the second dimension and the state variables and shocks as the other dimensions.
+Return the solution of the model. In the linear case it returns the linearised solution and the non stochastic steady state (NSSS) of the model. In the nonlinear case (higher order perturbation) the function returns a multidimensional array with the endogenous variables as the second dimension and the state variables, shocks, and perturbation parameter (:Volatility) in the case of higher order solutions as the other dimensions.
+
+The values of the output represent the NSSS in the case of a linear solution and below it the effect that deviations from the NSSS of the respective past states, shocks, and perturbation parameter have (perturbation parameter = 1) on the present value (NSSS deviation) of the model variables.
 
 # Arguments
 - $MODEL
@@ -1488,8 +1490,9 @@ Return the solution of the model. In the linear case it returns the linearised s
 - $ALGORITHM
 - $VERBOSE
 
-The returned `KeyedArray` shows as columns the endogenous variables inlcuding the auxilliary endogenous and exogenous variables (due to leads and lags > 1). The rows and other dimensions (depending on the chosen perturbation order) include the SS for the linear case only, followed by the states, and exogenous shocks. 
+The returned `KeyedArray` shows as columns the endogenous variables inlcuding the auxilliary endogenous and exogenous variables (due to leads and lags > 1). The rows and other dimensions (depending on the chosen perturbation order) include the NSSS for the linear case only, followed by the states, and exogenous shocks. 
 Subscripts following variable names indicate the timing (e.g. `variable₍₋₁₎`  indicates the variable being in the past). Superscripts indicate leads or lags (e.g. `variableᴸ⁽²⁾` indicates the variable being in lead by two periods). If no super- or subscripts follow the variable name, the variable is in the present.
+
 # Examples
 ```jldoctest
 using MacroModelling