Pandas: Convert Quarterly Data into Monthly Data
来源： https://stackoverflow.com/questions/61761785/pandas-convert-quarterly-data-into-monthly-data
time-series
Pandas: Convert Quarterly Data into Monthly Data
来源： https://stackoverflow.com/questions/61761785/pandas-convert-quarterly-data-into-monthly-data
Automatic way to highlight parts of a time series plot that have values higher than a certain threshold?
来源： https://stackoverflow.com/questions/56811184/automatic-way-to-highlight-parts-of-a-time-series-plot-that-have-values-higher-t
Automatic way to highlight parts of a time series plot that have values higher than a certain threshold?
来源： https://stackoverflow.com/questions/56811184/automatic-way-to-highlight-parts-of-a-time-series-plot-that-have-values-higher-t
R - auto.arima can xreg covariates contain missing NA values?
来源： https://stackoverflow.com/questions/63331366/r-time-series-auto-arima-xreg-dimension-is-zero-error
Time Series Forecasting with GARCH
问题 I am trying to forecast a time series object in R with GARCH(1,1) model. My goal is to hav 24 instances ahead forecast with the GARCH model. Although I am using a time series object while forecasting,I get the following error: Error in is.constant(y) : (list) object cannot be coerced to type 'double' Those are the commands that I am using: library(forecast) library(tseries) trainer1 <- ts(trainer, frequency=24) m1 <- garch(trainer1, order = c(1,1)) forecasts1 <- forecast(m1, h=24) And the
Time Series Forecasting with GARCH
问题 I am trying to forecast a time series object in R with GARCH(1,1) model. My goal is to hav 24 instances ahead forecast with the GARCH model. Although I am using a time series object while forecasting,I get the following error: Error in is.constant(y) : (list) object cannot be coerced to type 'double' Those are the commands that I am using: library(forecast) library(tseries) trainer1 <- ts(trainer, frequency=24) m1 <- garch(trainer1, order = c(1,1)) forecasts1 <- forecast(m1, h=24) And the
Create calendar table in SQL Server
问题 I am using Microsoft SQL Server 2012 and I am creating the following table: Clinic_code Clinic_name D D_days_passed ------------------------------------------------------ A123 NAME1 2018-12-01 1 A124 NAME2 2018-12-01 1 A125 NAME3 2018-12-01 1 [...] A123 NAME1 2018-12-02 2 A124 NAME2 2018-12-02 2 A125 NAME3 2018-12-02 2 [...] A123 NAME1 2018-12-03 3 A124 NAME2 2018-12-03 3 A125 NAME3 2018-12-03 3 I adapted the code here from @JohnCappelletti, but I'm struggling to include the 'D_days_passed'
How to use configurable moving average for forecasting in R
问题 I've 36 months of demand data dput(RawData) structure(list(ModelNo = c("a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a"), Month_Year = structure(c(1498867200, 1501545600, 1504224000, 1506816000, 1509494400, 1512086400, 1514764800, 1517443200, 1519862400, 1522540800, 1525132800, 1527811200, 1530403200, 1533081600, 1535760000, 1538352000, 1541030400, 1543622400,
How to use configurable moving average for forecasting in R
问题 I've 36 months of demand data dput(RawData) structure(list(ModelNo = c("a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a"), Month_Year = structure(c(1498867200, 1501545600, 1504224000, 1506816000, 1509494400, 1512086400, 1514764800, 1517443200, 1519862400, 1522540800, 1525132800, 1527811200, 1530403200, 1533081600, 1535760000, 1538352000, 1541030400, 1543622400,