time series analysis and missing data

General
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1

Hi, I have to analyze the geodetic time series (columns: dN (m), dE (m), dU (m) and h.) but I have missing data (about 10%).
Which packages to use for:

  1. ACF and PACF
  2. Trend
  3. seasonality
  4. White noise
  5. Random walk
  6. Smoothing
  7. Forecast

For missing data, how can i take advantage of this suggested code here?

Thanks.

Example of some data:

#site epoch date X (m) Y (m) Z (m) sX (m) sY (m) sZ (m) lat lon h. s_lat s_lon s_h. dN (m) dE (m) dU (m)
ARIA 2004.42077 04JUN03 4461242.7235 999519.9039 4432535.6353 0.0040 0.0015 0.0037 44.306007666 12.628301490 68.9231 0.0017 0.0013 0.0052 -0.0004 0.0000 0.0001
ARIA 2004.42350 04JUN04 4461242.7238 999519.9062 4432535.6278 0.0024 0.0009 0.0023 44.306007613 12.628301517 68.9183 0.0010 0.0008 0.0032 -0.0063 0.0022 -0.0047
ARIA 2004.42623 04JUN05 4461242.7260 999519.9079 4432535.6302 0.0023 0.0009 0.0023 44.306007613 12.628301533 68.9218 0.0010 0.0008 0.0031 -0.0063 0.0034 -0.0012
ARIA 2004.42896 04JUN06 4461242.7219 999519.9064 4432535.6265 0.0023 0.0009 0.0022 44.306007615 12.628301525 68.9161 0.0010 0.0008 0.0031 -0.0061 0.0028 -0.0069
ARIA 2004.43169 04JUN07 4461242.7253 999519.9076 4432535.6267 0.0023 0.0009 0.0022 44.306007594 12.628301531 68.9189 0.0010 0.0008 0.0030 -0.0084 0.0033 -0.0041
ARIA 2004.43443 04JUN08 4461242.7234 999519.9071 4432535.6270 0.0023 0.0009 0.0022 44.306007609 12.628301530 68.9176 0.0010 0.0008 0.0030 -0.0068 0.0032 -0.0054
ARIA 2004.43716 04JUN09 4461242.7239 999519.9076 4432535.6268 0.0023 0.0009 0.0022 44.306007603 12.628301535 68.9179 0.0010 0.0008 0.0031 -0.0074 0.0036 -0.0051
ARIA 2004.44536 04JUN12 4461242.7280 999519.9074 4432535.6296 0.0030 0.0012 0.0028 44.306007597 12.628301521 68.9227 0.0012 0.0010 0.0040 -0.0081 0.0025 -0.0003
ARIA 2004.45628 04JUN16 4461242.7230 999519.9083 4432535.6243 0.0053 0.0019 0.0047 44.306007592 12.628301546 68.9157 0.0021 0.0016 0.0069 -0.0087 0.0045 -0.0073

2

Hi @Ulysse, remember put a reproducible example for you data. dput()

Check this excellent book for times series:

You need select the best model, try first with Arima.

3

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