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Merge pull request #60 from Nixtla/ImprovedDocumentation2
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Intro paragraph for documentation, tutorial titles, gitignore protect…
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kdgutier committed Sep 30, 2022
2 parents 6f8da06 + dd5edb2 commit 94688e7
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1 change: 1 addition & 0 deletions .gitignore
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*.egg
MANIFEST

.last_checked
.gitattributes
.gitconfig
.DS_Store
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"cell_type": "markdown",
"metadata": {},
"source": [
"# Bootstrapped Probabilistic forecasts for Australian domestic tourism"
"# 5. Reconciled Probabilistic Forecasts (Bootstrap)"
]
},
{
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"metadata": {},
"outputs": [],
"source": [
"%%capture\n",
"%%captureBootstrapped\n",
"!pip install hierarchicalforecast\n",
"!pip install -U statsforecast numba statsmodels matplotlib"
]
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2 changes: 1 addition & 1 deletion nbs/examples/AustralianDomesticTourism-Intervals.ipynb
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"cell_type": "markdown",
"metadata": {},
"source": [
"# Probabilistic forecasts for Australian domestic tourism"
"# 4. Reconciled Probabilistic Forecasts (Normality)"
]
},
{
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2 changes: 1 addition & 1 deletion nbs/examples/AustralianDomesticTourism.ipynb
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"cell_type": "markdown",
"metadata": {},
"source": [
"# Forecasting Australian domestic tourism"
"# 2. R's Fable/HTS Replication1"
]
},
{
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2 changes: 1 addition & 1 deletion nbs/examples/AustralianPrisonPopulation.ipynb
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"cell_type": "markdown",
"metadata": {},
"source": [
"# Forecasting Australian prison population"
"# 3. R's Fable/HTS Replication2"
]
},
{
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2 changes: 1 addition & 1 deletion nbs/examples/TourismSmall.ipynb
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"id": "843cf8de-d678-4243-a8af-d78439058e6a",
"metadata": {},
"source": [
"# Hierarchical Reconciliation for TourismSmall dataset"
"# 1. Reconciliation Quick Start"
]
},
{
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6 changes: 4 additions & 2 deletions nbs/index.ipynb
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"id": "018f6145-b103-4f3e-b4cd-0aab4d8bbdb7",
"metadata": {},
"source": [
"# Hierarchical 👑 Forecast"
"# 👑 Hierarchical Forecast"
]
},
{
"cell_type": "markdown",
"id": "112249bc-95d7-42bd-9eb9-b6bb7dda5b20",
"metadata": {},
"source": [
"**HierarchicalForecast** offers a collection of reconciliation methods, including `BottomUp`, `TopDown`, `MiddleOut`, `MinTrace` and `ERM`. "
"Large collections of time series organized into structures at different aggregation levels often require their forecasts to follow their aggregation constraints, which poses the challenge of creating novel algorithms capable of coherent forecasts.\n",
"\n",
"**HierarchicalForecast** offers a collection of reconciliation methods, including `BottomUp`, `TopDown`, `MiddleOut`, `MinTrace` and `ERM`. Along with data wrangling, evaluation and visualization tools for grouped and hierarchical series."
]
},
{
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