How to model non-linear demand function?2019 Community Moderator ElectionCombining Linear Regression and Time SeriesHow can I get a forecasting model to improve its forecasts over time instead of fitting to training data?Exploration vs exploitation tradeoff to find a price that maximizes revenueHow to build a predictive model on Time series dataDemand Forecasting for Multiple Products Across Thousands of StoresAnalysing spikes in demand to forecast future demandModelling promotions for demand forecastingdemand forecast for B2Bforecast product demand in one week using machine learning approachMultivariate Sales forecasting for intermittent time series
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How to model non-linear demand function?
2019 Community Moderator ElectionCombining Linear Regression and Time SeriesHow can I get a forecasting model to improve its forecasts over time instead of fitting to training data?Exploration vs exploitation tradeoff to find a price that maximizes revenueHow to build a predictive model on Time series dataDemand Forecasting for Multiple Products Across Thousands of StoresAnalysing spikes in demand to forecast future demandModelling promotions for demand forecastingdemand forecast for B2Bforecast product demand in one week using machine learning approachMultivariate Sales forecasting for intermittent time series
$begingroup$
I am trying to build a dynamic pricing algorithm on intermittent data (a lot of zeros between non-zero values). I have on average 100 non-zero data points for each product. 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 relationships tend 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.
[Update 23/03/2019 : Added images/tables for elaborating Dynamic pricing]
The input is a intermittent sales data that looks something like the example shown below for most products.
(Intermittent demand image courtesy to)
Using Dynamic pricing, I would like to model the price-demand relation like the one shown below. Important : Linear demand are not realistic and in my case, the demand for my case non-linear.
(Linear demand image from)
In the end, I hope to create a model that can tell me what the optimal price is given a certain demand.
(Optimal demand image from
r time-series regression forecasting
asked Mar 21 at 13:52
thulungairthulungair
64
New contributor
thulungair is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
|
show 1 more comment
$begingroup$
I am trying to build a dynamic pricing algorithm on intermittent data (a lot of zeros between non-zero values). I have on average 100 non-zero data points for each product. 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 relationships tend 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.
[Update 23/03/2019 : Added images/tables for elaborating Dynamic pricing]
The input is a intermittent sales data that looks something like the example shown below for most products.
(Intermittent demand image courtesy to)
Using Dynamic pricing, I would like to model the price-demand relation like the one shown below. Important : Linear demand are not realistic and in my case, the demand for my case non-linear.
(Linear demand image from)
In the end, I hope to create a model that can tell me what the optimal price is given a certain demand.
(Optimal demand image from
r time-series regression forecasting
asked Mar 21 at 13:52
thulungairthulungair
64
New contributor
thulungair is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
$begingroup$
Have you tried RNN (LSTM or GRU) models ? These should be able to capture non-linear relationships in time series.
$endgroup$
– Shamit Verma
Mar 22 at 4:21
$begingroup$
It is not really clear what you want. Could you give an example what you data looks like and what you want to achieve?
$endgroup$
– MachineLearner
Mar 22 at 9:19
$begingroup$
@ShamitVerma I think any RNN models would be an overkill because I do not have much data. Maybe it would have been smarter for mention it in the question.
$endgroup$
– thulungair
Mar 23 at 13:26
$begingroup$
@MachineLearner I will edit my question to include a general example
$endgroup$
– thulungair
Mar 23 at 14:20
$begingroup$
How much data is availalbe for training ?
$endgroup$
– Shamit Verma
Mar 23 at 14:25
|
show 1 more comment
$begingroup$
I am trying to build a dynamic pricing algorithm on intermittent data (a lot of zeros between non-zero values). I have on average 100 non-zero data points for each product. 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 relationships tend 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.
[Update 23/03/2019 : Added images/tables for elaborating Dynamic pricing]
The input is a intermittent sales data that looks something like the example shown below for most products.
(Intermittent demand image courtesy to)
Using Dynamic pricing, I would like to model the price-demand relation like the one shown below. Important : Linear demand are not realistic and in my case, the demand for my case non-linear.
(Linear demand image from)
In the end, I hope to create a model that can tell me what the optimal price is given a certain demand.
(Optimal demand image from
r time-series regression forecasting
asked Mar 21 at 13:52
thulungairthulungair
64
New contributor
thulungair is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
I am trying to build a dynamic pricing algorithm on intermittent data (a lot of zeros between non-zero values). I have on average 100 non-zero data points for each product. 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 relationships tend 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.
[Update 23/03/2019 : Added images/tables for elaborating Dynamic pricing]
The input is a intermittent sales data that looks something like the example shown below for most products.
(Intermittent demand image courtesy to)
Using Dynamic pricing, I would like to model the price-demand relation like the one shown below. Important : Linear demand are not realistic and in my case, the demand for my case non-linear.
(Linear demand image from)
In the end, I hope to create a model that can tell me what the optimal price is given a certain demand.
(Optimal demand image from
r time-series regression forecasting
r time-series regression forecasting
asked Mar 21 at 13:52
thulungairthulungair
64
New contributor
thulungair is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked Mar 21 at 13:52
thulungairthulungair
64
New contributor
thulungair is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
edited Mar 23 at 14:57
thulungair
asked Mar 21 at 13:52
thulungairthulungair
64
New contributor
thulungair is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked Mar 21 at 13:52
thulungairthulungair
64
asked Mar 21 at 13:52
thulungairthulungair
64
64
New contributor
thulungair is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
thulungair is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
thulungair is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$begingroup$
Have you tried RNN (LSTM or GRU) models ? These should be able to capture non-linear relationships in time series.
$endgroup$
– Shamit Verma
Mar 22 at 4:21
$begingroup$
It is not really clear what you want. Could you give an example what you data looks like and what you want to achieve?
$endgroup$
– MachineLearner
Mar 22 at 9:19
$begingroup$
@ShamitVerma I think any RNN models would be an overkill because I do not have much data. Maybe it would have been smarter for mention it in the question.
$endgroup$
– thulungair
Mar 23 at 13:26
$begingroup$
@MachineLearner I will edit my question to include a general example
$endgroup$
– thulungair
Mar 23 at 14:20
$begingroup$
How much data is availalbe for training ?
$endgroup$
– Shamit Verma
Mar 23 at 14:25
|
show 1 more comment
$begingroup$
Have you tried RNN (LSTM or GRU) models ? These should be able to capture non-linear relationships in time series.
$endgroup$
– Shamit Verma
Mar 22 at 4:21
$begingroup$
It is not really clear what you want. Could you give an example what you data looks like and what you want to achieve?
$endgroup$
– MachineLearner
Mar 22 at 9:19
$begingroup$
@ShamitVerma I think any RNN models would be an overkill because I do not have much data. Maybe it would have been smarter for mention it in the question.
$endgroup$
– thulungair
Mar 23 at 13:26
$begingroup$
@MachineLearner I will edit my question to include a general example
$endgroup$
– thulungair
Mar 23 at 14:20
$begingroup$
How much data is availalbe for training ?
$endgroup$
– Shamit Verma
Mar 23 at 14:25
$begingroup$
Have you tried RNN (LSTM or GRU) models ? These should be able to capture non-linear relationships in time series.
$endgroup$
– Shamit Verma
Mar 22 at 4:21
$begingroup$
Have you tried RNN (LSTM or GRU) models ? These should be able to capture non-linear relationships in time series.
$endgroup$
– Shamit Verma
Mar 22 at 4:21
$begingroup$
It is not really clear what you want. Could you give an example what you data looks like and what you want to achieve?
$endgroup$
– MachineLearner
Mar 22 at 9:19
$begingroup$
It is not really clear what you want. Could you give an example what you data looks like and what you want to achieve?
$endgroup$
– MachineLearner
Mar 22 at 9:19
$begingroup$
@ShamitVerma I think any RNN models would be an overkill because I do not have much data. Maybe it would have been smarter for mention it in the question.
$endgroup$
– thulungair
Mar 23 at 13:26
$begingroup$
@ShamitVerma I think any RNN models would be an overkill because I do not have much data. Maybe it would have been smarter for mention it in the question.
$endgroup$
– thulungair
Mar 23 at 13:26
$begingroup$
@MachineLearner I will edit my question to include a general example
$endgroup$
– thulungair
Mar 23 at 14:20
$begingroup$
@MachineLearner I will edit my question to include a general example
$endgroup$
– thulungair
Mar 23 at 14:20
$begingroup$
How much data is availalbe for training ?
$endgroup$
– Shamit Verma
Mar 23 at 14:25
$begingroup$
How much data is availalbe for training ?
$endgroup$
– Shamit Verma
Mar 23 at 14:25
|
show 1 more comment
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$begingroup$
Have you tried RNN (LSTM or GRU) models ? These should be able to capture non-linear relationships in time series.
$endgroup$
– Shamit Verma
Mar 22 at 4:21
$begingroup$
It is not really clear what you want. Could you give an example what you data looks like and what you want to achieve?
$endgroup$
– MachineLearner
Mar 22 at 9:19
$begingroup$
@ShamitVerma I think any RNN models would be an overkill because I do not have much data. Maybe it would have been smarter for mention it in the question.
$endgroup$
– thulungair
Mar 23 at 13:26
$begingroup$
@MachineLearner I will edit my question to include a general example
$endgroup$
– thulungair
Mar 23 at 14:20
$begingroup$
How much data is availalbe for training ?
$endgroup$
– Shamit Verma
Mar 23 at 14:25