How to model non-linear demand function?
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I am trying to build a dynamic pricing algorithm on intermittent data (a lot of zeros between non-zero values). However, it seems to be quite difficult to predict the right price due to various reasons (non-regular demand, intermittent data, noises etc) so for the first step, I am trying to forecast the demand of each product using MAPA from Nikolaos Kourentzes. I hope to use this demand forecast and price-demand relation to predict the optimal price.
However, in practice these price-demand relation tends to be non-linear so I was wondering if anyone here could guide me to papers/resources that I can follow to train non-linear model(s) on the price-demand relationship with intermittent demand data. Ideally, the trained model should be optimizable for price.
r time-series regression forecasting
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$begingroup$
I am trying to build a dynamic pricing algorithm on intermittent data (a lot of zeros between non-zero values). However, it seems to be quite difficult to predict the right price due to various reasons (non-regular demand, intermittent data, noises etc) so for the first step, I am trying to forecast the demand of each product using MAPA from Nikolaos Kourentzes. I hope to use this demand forecast and price-demand relation to predict the optimal price.
However, in practice these price-demand relation tends to be non-linear so I was wondering if anyone here could guide me to papers/resources that I can follow to train non-linear model(s) on the price-demand relationship with intermittent demand data. Ideally, the trained model should be optimizable for price.
r time-series regression forecasting
New contributor
$endgroup$
add a comment |
$begingroup$
I am trying to build a dynamic pricing algorithm on intermittent data (a lot of zeros between non-zero values). However, it seems to be quite difficult to predict the right price due to various reasons (non-regular demand, intermittent data, noises etc) so for the first step, I am trying to forecast the demand of each product using MAPA from Nikolaos Kourentzes. I hope to use this demand forecast and price-demand relation to predict the optimal price.
However, in practice these price-demand relation tends to be non-linear so I was wondering if anyone here could guide me to papers/resources that I can follow to train non-linear model(s) on the price-demand relationship with intermittent demand data. Ideally, the trained model should be optimizable for price.
r time-series regression forecasting
New contributor
$endgroup$
I am trying to build a dynamic pricing algorithm on intermittent data (a lot of zeros between non-zero values). However, it seems to be quite difficult to predict the right price due to various reasons (non-regular demand, intermittent data, noises etc) so for the first step, I am trying to forecast the demand of each product using MAPA from Nikolaos Kourentzes. I hope to use this demand forecast and price-demand relation to predict the optimal price.
However, in practice these price-demand relation tends to be non-linear so I was wondering if anyone here could guide me to papers/resources that I can follow to train non-linear model(s) on the price-demand relationship with intermittent demand data. Ideally, the trained model should be optimizable for price.
r time-series regression forecasting
r time-series regression forecasting
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New contributor
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asked 12 hours ago
thulungairthulungair
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