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LICENSE

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+MIT License
+
+Copyright (c) 2023 Arthur Brigatto <[email protected]> and contributors
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

Project.toml

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+name = "SeasonalNaive"
+uuid = "4e5a55a7-a1e0-4c7c-8281-8d51e13076a6"
+authors = ["Arthur Brigatto <[email protected]> and contributors"]
+version = "1.0.0-DEV"
+
+[compat]
+julia = "1"
+
+[extras]
+Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+
+[targets]
+test = ["Test"]

README.md

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+# SeasonalNaive
+
+[![Stable](https://img.shields.io/badge/docs-stable-blue.svg)](https://arthur-brigatto.github.io/SeasonalNaive.jl/stable/)
+[![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://arthur-brigatto.github.io/SeasonalNaive.jl/dev/)
+[![Build Status](https://github.com/arthur-brigatto/SeasonalNaive.jl/actions/workflows/CI.yml/badge.svg?branch=master)](https://github.com/arthur-brigatto/SeasonalNaive.jl/actions/workflows/CI.yml?query=branch%3Amaster)
+[![Coverage](https://codecov.io/gh/arthur-brigatto/SeasonalNaive.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/arthur-brigatto/SeasonalNaive.jl)
+
+A Julia package to forecast time series using the seasonal naïve model. 
+
+Forecasts are done using the following equation:
+
+$`\hat{y}_{T+k} = y_{T+k-m*(\lfloor \frac{k+1}{m}\rfloor + 1)}`$
+
+where $m$ is the seasonal period.

docs/Project.toml

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+[deps]
+Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
+SeasonalNaive = "4e5a55a7-a1e0-4c7c-8281-8d51e13076a6"

docs/make.jl

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+using SeasonalNaive
+using Documenter
+
+DocMeta.setdocmeta!(SeasonalNaive, :DocTestSetup, :(using SeasonalNaive); recursive=true)
+
+makedocs(;
+    modules=[SeasonalNaive],
+    authors="Arthur Brigatto <[email protected]> and contributors",
+    repo="https://github.com/arthur-brigatto/SeasonalNaive.jl/blob/{commit}{path}#{line}",
+    sitename="SeasonalNaive.jl",
+    format=Documenter.HTML(;
+        prettyurls=get(ENV, "CI", "false") == "true",
+        canonical="https://arthur-brigatto.github.io/SeasonalNaive.jl",
+        edit_link="master",
+        assets=String[],
+    ),
+    pages=[
+        "Home" => "index.md",
+    ],
+)
+
+deploydocs(;
+    repo="github.com/arthur-brigatto/SeasonalNaive.jl",
+    devbranch="master",
+)

docs/src/index.md

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+```@meta
+CurrentModule = SeasonalNaive
+```
+
+# SeasonalNaive
+
+Documentation for [SeasonalNaive](https://github.com/arthur-brigatto/SeasonalNaive.jl).
+
+```@index
+```
+
+```@autodocs
+Modules = [SeasonalNaive]
+```

src/SeasonalNaive.jl

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+module SeasonalNaive
+
+    include("forecast.jl")
+
+    export forecast
+
+end

src/forecast.jl

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+function forecast(past_data::Vector{Float64}, seasonality::Int64, steps_ahead::Int64)
+
+    forecasts = zeros(steps_ahead)::Vector{Float64}
+    for k in 1:steps_ahead
+        forecast = past_data[Int(end + k - seasonality*(floor((k - 1)/seasonality)+1))]
+        forecasts[k] = forecast
+    end
+
+    return forecasts
+
+end

test/runtests.jl

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+using SeasonalNaive
+using Test
+
+@testset "SeasonalNaive.jl" begin
+    @testset "forecast season 120" begin
+        past_data = rand(120)
+        forecasted = forecast(past_data, 120, 120)
+        @test past_data == forecasted
+    end
+    @testset "forecast season 12" begin
+        past_data = rand(60)
+        forecasted = forecast(past_data, 12, 12)
+        @test past_data[end-11: end] == forecasted
+    end
+    @testset "forecast season 13" begin
+        past_data = rand(60)
+        forecasted = forecast(past_data, 13, 26)
+        @test [past_data[end-12: end]; past_data[end-12: end]] == forecasted
+    end
+end