We can generate prediction intervals using the level
parameter in the
forecast
method. It takes any values between 0 and 100, including
decimal numbers.
👍 Use an Azure AI endpoint
To use an Azure AI endpoint, remember to set also the
base_url
argument:
nixtla_client = NixtlaClient(base_url="you azure ai endpoint", api_key="your api_key")
📘 Available models in Azure AI
If you are using an Azure AI endpoint, please be sure to set
model="azureai"
:
nixtla_client.forecast(..., model="azureai")
For the public API, we support two models:
timegpt-1
andtimegpt-1-long-horizon
.By default,
timegpt-1
is used. Please see this tutorial on how and when to usetimegpt-1-long-horizon
.
For more details on uncertainty quantification, read our tutorials on using quantile forecasts and prediction intervals.
We can generate prediction intervals using the level
parameter in the
forecast
method. It takes any values between 0 and 100, including
decimal numbers.
👍 Use an Azure AI endpoint
To use an Azure AI endpoint, remember to set also the
base_url
argument:
nixtla_client = NixtlaClient(base_url="you azure ai endpoint", api_key="your api_key")
📘 Available models in Azure AI
If you are using an Azure AI endpoint, please be sure to set
model="azureai"
:
nixtla_client.forecast(..., model="azureai")
For the public API, we support two models:
timegpt-1
andtimegpt-1-long-horizon
.By default,
timegpt-1
is used. Please see this tutorial on how and when to usetimegpt-1-long-horizon
.
For more details on uncertainty quantification, read our tutorials on using quantile forecasts and prediction intervals.