fix imports

src/Backtest/Forecast.jl

@@ -8,7 +8,9 @@ This struct represents a general forecaster that can be combined with others
 Can apply forecast to data with the following signature:
 forecastFunction(data::Vector{Real}, params::Real...; F::Int=1) -> Vector{Real}
 """
-struct Forecaster
+abstract type Forecaster end
+
+struct BaseForecaster <: Forecaster
 	forecastFunction::Function
 	params::Vector{Any}
 end

src/Backtest/forecast/ARIMA.jl

@@ -6,7 +6,7 @@ using Random
 using Distributions
 using StatsBase
 
-using ..Combine
+using ..Forecast: Forecaster
 
 """
 This function applies differencing to a time series
@@ -115,22 +115,6 @@ function arima(series, p::Int, d::Int, q::Int, reparameterise_window::Int = 0; F
 	return restored_series[(end-F+1):end]
 end
 
-"""
-This function returns a forecaster object that can be used with the Combine module
-
-Arguments:
-- p::int: The number of lags to consider
-- d::int: The order of differencing
-- q::int: Moving average order
-
-Returns:
-- Combined::Combine.Forecaster: The forecaster
-"""
-
-function ArimaForecaster(p::Int, d::Int, q::Int; reparameterise_window::Int = 0)
-	return Combine.Forecaster(arima, [p; d; q; reparameterise_window])
-end
-
 struct ArimaForecaster <: Forecaster
 	p::Int
 	d::Int

src/Backtest/forecast/Combine.jl

@@ -1,11 +1,12 @@
 module Combine
+using ..Forecast: Forecaster
 
 """
 This struct represents a combined forecaster that is a linear combination of other forecasters
 """
 struct CombinedForecaster <: Forecaster
-	forecasters::Vector{<:Forecaster}
-	weights::Vector{<:Real}
+	forecasters::Vector{T} where T <: Forecaster
+	weights::Vector{U} where U <: Real
 	CombinedForecaster(forecasters::Vector{Forecaster}, weights::Vector{<:Real}) = length(forecasters) == length(weights) ? new(forecasters, weights) : throw(ArgumentError("Length of forecasters and weights must be equal"))
 end
 

src/Backtest/forecast/Linear.jl

@@ -2,7 +2,7 @@ module Linear
 
 using DataFrames
 using RollingFunctions
-using ..Combine
+using ..Forecast: Forecaster
 
 """
 This function returns the parameters of a linear regression model that predicts