update jldoctest

Author: guilhermebodin

src/fit.jl

@@ -14,16 +14,16 @@ the [Optim.jl](https://github.com/JuliaNLSolvers/Optim.jl) optimization algortih
 # Example
 ```jldoctest
 julia> model = LocalLevel(rand(100))
-LocalLevel model
+LocalLevel
 
 julia> fit!(model)
-LocalLevel model
+LocalLevel
 
 julia> model = LocalLinearTrend(LinRange(1, 100, 100) + rand(100))
-LocalLinearTrend model
+LocalLinearTrend
 
 julia> fit!(model; optimizer = Optimizer(StateSpaceModels.Optim.NelderMead()))
-LocalLinearTrend model
+LocalLinearTrend
 ```
 """
 function fit!(

src/hyperparameters.jl

@@ -195,18 +195,18 @@ Fill a model with user inputed initial points for hyperparameter optimzation.
 # Example
 ```jldoctest
 julia> model = LocalLevel(rand(100))
-LocalLevel model
+LocalLevel
 
 julia> get_names(model)
-2-element Array{String,1}:
+2-element Vector{String}:
  "sigma2_ε"
  "sigma2_η"
 
 julia> set_initial_hyperparameters!(model, Dict("sigma2_η" => 100.0))
-LocalLevel model
+LocalLevel
 
 julia> model.hyperparameters.constrained_values
-2-element Array{Float64,1}:
+2-element Vector{Float64}::
  NaN  
  100.0
 ```
@@ -260,7 +260,7 @@ julia> model = LocalLevel(rand(100))
 LocalLevel model
 
 julia> get_names(model)
-2-element Array{String,1}:
+2-element Vector{String}:
  "sigma2_ε"
  "sigma2_η"
 

src/models/sarima.jl

@@ -89,7 +89,7 @@ In terms of a univariate structural model, this can be represented as
 # Example
 ```jldoctest
 julia> model = SARIMA(rand(100); order=(1,1,1), seasonal_order=(1,2,3,12))
-SARIMA(1, 1, 1)x(1, 2, 3, 12) model
+SARIMA(1, 1, 1)x(1, 2, 3, 12) with zero mean
 ```
 
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