time-series

问题 Problem: I have a data frame called FID (see below) that contains two columns for Year & Month, and Sighting_Frequency (counts of birds). The data frame contains 3 years of observations between 2015-2017 , indicating I have 36 months of data. I have run a Bayesian time series analysis with MCMC using the bsts() function in the bsts package (see the R-code below) by following the tutorial below. I want to produce a holdout Mean Absolute Percentage Error (MAPE) Plot as seen in the diagram below

问题 The bounty expires in 5 days . Answers to this question are eligible for a +50 reputation bounty. stats555 is looking for a canonical answer : I am using the R programming language. I am trying to use the "plotly" library to make interactive time series plots as shown in this tutorial over here : plotly.com/r/custom-buttons and plotly.com/r/cumulative-animations . I generated some artificial time series data that matches the structure of the data shown in the tutorial - now I am trying to

问题 I am working on building a time series in R programming language. I m having a zoo object which is follows: I 'd like to convert this into a weekly time series data for analysis and typed in the following code tt2<-as.ts(zz,freq=365.25/7,start=decimal_date(ymd("2018-01-01"))) tt2[is.na(tt2)]<-0 However, I get the following output: Time Series: Start = 17538 End = 18532 Frequency = 0.142857142857143 While I'd like to see the output in line with something like this: Time Series: Start = c(2018

问题 I am working on building a time series in R programming language. I m having a zoo object which is follows: I 'd like to convert this into a weekly time series data for analysis and typed in the following code tt2<-as.ts(zz,freq=365.25/7,start=decimal_date(ymd("2018-01-01"))) tt2[is.na(tt2)]<-0 However, I get the following output: Time Series: Start = 17538 End = 18532 Frequency = 0.142857142857143 While I'd like to see the output in line with something like this: Time Series: Start = c(2018

问题 I simulated some time series data in R, aggregated by every 8 days, and then tried to plot the results. However, the plots are not working. I have posted my code below: #load library library(xts) library(ggplot2) set.seed(123) #simulate data property_damages_in_dollars <- rnorm(731,100,10) date_decision_made = seq(as.Date("2014/1/1"), as.Date("2016/1/1"),by="day") date_decision_made <- format(as.Date(date_decision_made), "%Y/%m/%d") final_data <- data.frame(date_decision_made, property

问题 I am using the R programming language. I found some examples on the plotly r website that I am trying to replicate: https://plotly.com/r/cumulative-animations/ and https://plotly.com/r/custom-buttons/ I created some artificial time series data: library(xts) library(ggplot2) library(dplyr) library(plotly) #create data #time series 1 date_decision_made = seq(as.Date("2014/1/1"), as.Date("2016/1/1"),by="day") date_decision_made <- format(as.Date(date_decision_made), "%Y/%m/%d") property_damages

问题 I am using the R programming language. I found some examples on the plotly r website that I am trying to replicate: https://plotly.com/r/cumulative-animations/ and https://plotly.com/r/custom-buttons/ I created some artificial time series data: library(xts) library(ggplot2) library(dplyr) library(plotly) #create data #time series 1 date_decision_made = seq(as.Date("2014/1/1"), as.Date("2016/1/1"),by="day") date_decision_made <- format(as.Date(date_decision_made), "%Y/%m/%d") property_damages

问题 I am wondering if there is an easy way to create a lag (or lead) of a time series variable in Julia according to a by group or condition? For example: I have a dataset of the following form julia> df1 = DataFrame(var1=["a","a","a","a","b","b","b","b"], var2=[0,1,2,3,0,1,2,3]) 8×2 DataFrame │ Row │ var1 │ var2 │ │ │ String │ Int64 │ ├─────┼────────┼───────┤ │ 1 │ a │ 0 │ │ 2 │ a │ 1 │ │ 3 │ a │ 2 │ │ 4 │ a │ 3 │ │ 5 │ b │ 0 │ │ 6 │ b │ 1 │ │ 7 │ b │ 2 │ │ 8 │ b │ 3 │ And I want to create a

问题 I am wondering if there is an easy way to create a lag (or lead) of a time series variable in Julia according to a by group or condition? For example: I have a dataset of the following form julia> df1 = DataFrame(var1=["a","a","a","a","b","b","b","b"], var2=[0,1,2,3,0,1,2,3]) 8×2 DataFrame │ Row │ var1 │ var2 │ │ │ String │ Int64 │ ├─────┼────────┼───────┤ │ 1 │ a │ 0 │ │ 2 │ a │ 1 │ │ 3 │ a │ 2 │ │ 4 │ a │ 3 │ │ 5 │ b │ 0 │ │ 6 │ b │ 1 │ │ 7 │ b │ 2 │ │ 8 │ b │ 3 │ And I want to create a

问题 I am wondering if there is an easy way to create a lag (or lead) of a time series variable in Julia according to a by group or condition? For example: I have a dataset of the following form julia> df1 = DataFrame(var1=["a","a","a","a","b","b","b","b"], var2=[0,1,2,3,0,1,2,3]) 8×2 DataFrame │ Row │ var1 │ var2 │ │ │ String │ Int64 │ ├─────┼────────┼───────┤ │ 1 │ a │ 0 │ │ 2 │ a │ 1 │ │ 3 │ a │ 2 │ │ 4 │ a │ 3 │ │ 5 │ b │ 0 │ │ 6 │ b │ 1 │ │ 7 │ b │ 2 │ │ 8 │ b │ 3 │ And I want to create a