问R刚时间序列-图中的奇异时间轴

EN

df    = read.csv('https://github.com/zhaokg/Rbeast/raw/master/R/SampleData/pm10_1658112168.csv',header=FALSE,skip=3)

dates = as.Date(df[,1], "%d/%m/%Y")  # the 1st col is dates
Y     = df[,2:ncol(df)]              # the rest are PM10 data for the several sample sites
                                     # e.g., Y[,1] for the first region (WOLLONGONG)


library(Rbeast)

o = beast.irreg(log(Y[,1]),time=dates,deltat=1/12, freq=12, tseg.min=3, sseg.min=6)

# log(Y[,1]) :  Log-transformation may help if data is skewed bcz the BEAST model 
                assumes Gaussian errors;
# time=dates :  Use the 'time' arg to supply the times of individual data points.
               Alternatively, the `beast123' function also handles date strings of different formats
# deltat=1/12:  Aggregate the daily time series into a regular one at the interval 
                of 1 month=1/12 year
# freq=12 :    The period is 1 year, which is 12 data points (1.0/deltat=12)
# tseg.min:     The minimum trend segment length allowed in the changepoint detection is 3 data points (3 months) 
                -- the results MAY be sensitive to this parameter
# sseg.min:     The minimum seasonal segment length allowed in the changepoint detection is 6 data points (6 months) 
                -- the results MAY be sensitive to this parameter

plot(o)




# For sure, the daily time series can be re-sampled/aggregated to a different time interval
# Below, it is aggregated into a half monthly time series (dT=1/24 year), and the number
# of data points per period is freq=1.0 year/dT=24
o = beast.irreg( log(Y[,1]),time=dates,  deltat = 1/24, freq=24, tseg.min=12, sseg.min=12)
plot(o)

# Aggregated to a weekly time series (e.g., dT=7 / 365  year: the unit again is year), 
# and freq=1 year/ dT = 365/7.
# tcp.minmax=c(0,10) :  the min and max numbers of changepoints allowed in the trend component
o = beast.irreg( log(Y[,1]),time=dates,deltat=7/365,freq=365/7, tcp.minmax=c(0,15),tseg.min=5, sseg.min=20,ocp=10)
plot(o)


# Finally if you want to run on the daily interval. Specify the dT=deltat=1/365 year, and 
# freq = period/dT= 1.0 year/(1/365)year =365. Bcz the raw data is daily, 
# the majority of the raw data is kept intact during the aggregation except when 
# there is a leap year (the last two days of the leap year are merged into a single day)

o = beast.irreg( log(Y[,1]),time=dates,  deltat = 1/365, freq=365/1,  tseg.min=30, sseg.min=180)
plot(o)

# Use 'ocp' to specify the maximum number of spikes (either upward or downward) to be allowed in the outlier/spike component

o = beast.irreg(Y[,1],time=dates,  deltat = 1/365, freq=365/1,  tseg.min=30, sseg.min=180, ocp=10)
plot(o)