facebook-prophet

Generating long-term forecasts including prophet and temporal aggregation (thief)

由 懵懂的女人 提交于 2020-12-15 04:55:04
问题 I just started to use {fable} and the {tidyverts} family of tools and so far it's going quite well. I'm currently interested in producing long term probabilistic forecasts from daily data (with a monthly or quarterly resolution being fine or preferred). My understanding is, that temporal aggregation could help reduce model uncertainty and also propagate known daily influences (especially holiday effects) to the e.g. quarterly level and improve accuracy that way. For the daily data I plan on

Generating long-term forecasts including prophet and temporal aggregation (thief)

由 旧时模样 提交于 2020-12-15 04:54:13
问题 I just started to use {fable} and the {tidyverts} family of tools and so far it's going quite well. I'm currently interested in producing long term probabilistic forecasts from daily data (with a monthly or quarterly resolution being fine or preferred). My understanding is, that temporal aggregation could help reduce model uncertainty and also propagate known daily influences (especially holiday effects) to the e.g. quarterly level and improve accuracy that way. For the daily data I plan on

How to install fbprophet for Python 3.7 (anaconda distribution)

由 扶醉桌前 提交于 2020-12-13 00:45:01
问题 I attempted to use fbprophet for time series analysis using Python. I ran from fbprophet import Prophet but got No module named 'fbprophet' I think fbprophet is not part of packages that comes with anaconda distribution I went ahead to install fbprophet but got this error message No module named 'fbprophet' I am on Windows 10, 64 bits I install anaconda distribution of anaconda 3.7 I have ran conda install -c conda-forge fbprophet and conda install -c conda-forge/label/cf201901 fbprophet on

How to install fbprophet for Python 3.7 (anaconda distribution)

由 白昼怎懂夜的黑 提交于 2020-12-13 00:44:26
问题 I attempted to use fbprophet for time series analysis using Python. I ran from fbprophet import Prophet but got No module named 'fbprophet' I think fbprophet is not part of packages that comes with anaconda distribution I went ahead to install fbprophet but got this error message No module named 'fbprophet' I am on Windows 10, 64 bits I install anaconda distribution of anaconda 3.7 I have ran conda install -c conda-forge fbprophet and conda install -c conda-forge/label/cf201901 fbprophet on

How to change type of line in prophet plot?

由 谁说我不能喝 提交于 2020-06-16 17:32:01
问题 Facebook's Prophet in R (there's also a Python version) is used to generate time series forecasts. A model m is created by: m <- prophet(df) future <- make_future_dataframe(m, periods = 365) forecast <- predict(m, future) plot(m, forecast) Which returns a very nicely formatted graph, like: I would like to change the line type, to get not dots but a usual thin line. I had tried this lines(m$history$y,lty=1) but got an error In doTryCatch(return(expr), name, parentenv, handler) Are there are

Forecasting with facebook prophet using Pandas udf in spark

由 爱⌒轻易说出口 提交于 2020-05-17 08:46:42
问题 I am trying to use Facebook prophet in spark in an Zeppelin environment and I have tried to follow the exact steps from https://github.com/facebook/prophet/issues/517, However, i get errors like below. I am simply not sure what am I to correct here or how to debug this. My data contains a datetime features called ds , volume that I want to predict y and the segment and I am trying to build a model for each segment. File"/hadoop14/yarn/nm/usercache/khasbab/appcache/application_1588090646020

统计学预测模型——通过 Python 代码实现时间序列数据分析

由 混江龙づ霸主 提交于 2020-04-11 18:55:19
在本篇中，我们将展示使用 Python 统计学模型进行时间序列数据分析。 问题描述 目标：根据两年以上的每日广告支出历史数据，提前预测两个月的广告支出金额。 原始数据：2017-01-01 到 2019-09-23 期间的每日广告支出。 数据准备：划分训练集和测试集。 df1 = data[['Date','Spend']].set_index('Date') train = df1.iloc[:933,:] test = df1.iloc[933:,:] test.shape,train.shape 测试集大小：(63,1)；训练集大小：(933,1)。 1、综述 时间序列分析常用统计模型 单变量时间序列统计学模型，如：平均方法、平滑方法、有/无季节性条件的 ARIMA 模型。 多变量时间序列统计学模型，如：外生回归变量、VAR。 附加或组件模型，如：Facebook Prophet、ETS。 结构化时间序列模型，如：贝叶斯结构化时间序列模型、分层时间序列模型。 在本篇文章中，我们主要关注 SARIMA 和 Holt-winters 方法。 单变量时间序列统计学模型的关键要素 如果我们想要对时间序列数据进行上述统计学模型分析，需要进行一系列处理使得： (1)数据均值 (2)数据方差 (3)数据自协方差 这三个指标不依赖于时间项。即时间序列数据具有平稳性。

Adding extra regressor in Prophet

由 為{幸葍}努か 提交于 2020-02-06 15:46:51
问题 I hope I'll find a way to ask a question. I have data of a store's income with a 3-4 year history. My goal is to forecast next two months. I'm trying to achieve this with prophet, and so far it's going well. I have a regressor I want to use to improve my forecast but I'm not sure how to use it the best way I can. My regresor is different levels of impact on the stores income where 1 equals no impact, and 1,20 for example equals, 20 percent increase on that day. 0,8 would mean that there would

Adding extra regressor in Prophet

由 这一生的挚爱 提交于 2020-02-06 15:46:27
问题 I hope I'll find a way to ask a question. I have data of a store's income with a 3-4 year history. My goal is to forecast next two months. I'm trying to achieve this with prophet, and so far it's going well. I have a regressor I want to use to improve my forecast but I'm not sure how to use it the best way I can. My regresor is different levels of impact on the stores income where 1 equals no impact, and 1,20 for example equals, 20 percent increase on that day. 0,8 would mean that there would

using Prophet on netCDF file using xarray

由 a 夏天 提交于 2020-01-16 05:39:06
问题 I have a 'netCDF' file which I have read with xarray and I want to use to generate a forecast for each pixel in the file. import xarray as xr from fbprophet import Prophet import time with xr.open_dataset('avi.nc', chunks={'y': 2, 'x':2}) as avi: print(avi) <xarray.Dataset> Dimensions: (ds: 104, lat: 213, lon: 177) Coordinates: * lat (lat) float64 -2.711e+06 -2.711e+06 -2.711e+06 -2.711e+06 ... * lon (lon) float64 1.923e+06 1.924e+06 1.924e+06 1.924e+06 1.924e+06 ... * ds (ds) object '1999-07
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