Row 6458

Row ID: 6458 | Dataset Entry | Axioma AXP Content Repository

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Hi all,

I will soon start to work on a project with multivariate input to forecast multiple outputs. The idea is that the variables indirectly influence each other, i.e. based on car information: year-make-model-supply-price, I want to forecast supply and price with confidence intervals for each segment. Supply affects price which is why I don't want to separate them.

Any resources you would recommend to someone fairly new to time series? Thank you!!

FieldValue
text Hi all, I will soon start to work on a project with multivariate input to forecast multiple outputs. The idea is that the variables indirectly influence each other, i.e. based on car information: year-make-model-supply-price, I want to forecast supply and price with confidence intervals for each segment. Supply affects price which is why I don't want to separate them. Any resources you would recommend to someone fairly new to time series? Thank you!!
label r/datascience
dataType post
communityName r/datascience
datetime 2024-05-10
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url_encoded Z0FBQUFBQm5Lak9HX0FGMnZPRGdLNFAxYm5yNEcyTm5EWmNRdHJOVzZPSlFJcFd6SGExQnItLWtwUGthZ3o4VU51bVU1c2lIc0lXUnZZbThUVHNjaVE1NnZTTDl0X2wxTnZ4ZHhDeHBRbTdlQnpVMEZ3R3RNVkhkTEtZMkFNV0RaaDFtT1hsWUNmMlB2LThGdEZCUnhrUEN4bHhIR3RoZmppN3EtU2M5OXU2cjRVNHlNc1pSVjAxMTZOS2hVcl9PV1NzQXA4MnBqRlhzM3VyZHZId3h5dC1oNkFub2JtSjB3dz09

Raw Record

{
  "text": "Hi all,\n\nI will soon start to work on a project with multivariate input to forecast multiple outputs. The idea is that the variables indirectly influence each other, i.e. based on car information: year-make-model-supply-price, I want to forecast supply and price with confidence intervals for each segment. Supply affects price which is why I don't want to separate them.\n\nAny resources you would recommend to someone fairly new to time series? Thank you!!",
  "label": "r/datascience",
  "dataType": "post",
  "communityName": "r/datascience",
  "datetime": "2024-05-10",
  "username_encoded": "Z0FBQUFBQm5LakwybDR4Y0FGNWVCUzVEZnFCSkVUNzFHcHg2bWxTRGVaLUYxcUFLRVdSMmc1RFdwVjBjQkQ3MVRvMG0yb2ZPMkNsTzFjZGlZemMycklQSGNIcXR5VjBTQlhZUFJ0VGEtLXR5VDNZZTZoN1RRUDA9",
  "url_encoded": "Z0FBQUFBQm5Lak9HX0FGMnZPRGdLNFAxYm5yNEcyTm5EWmNRdHJOVzZPSlFJcFd6SGExQnItLWtwUGthZ3o4VU51bVU1c2lIc0lXUnZZbThUVHNjaVE1NnZTTDl0X2wxTnZ4ZHhDeHBRbTdlQnpVMEZ3R3RNVkhkTEtZMkFNV0RaaDFtT1hsWUNmMlB2LThGdEZCUnhrUEN4bHhIR3RoZmppN3EtU2M5OXU2cjRVNHlNc1pSVjAxMTZOS2hVcl9PV1NzQXA4MnBqRlhzM3VyZHZId3h5dC1oNkFub2JtSjB3dz09"
}
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