Now, a lot of my FOMO comes from the fact that I work. I work at 6 a.m. every day of pretty much every weekend. This means no going out the night before unless I want to be exhausted, and a lot of missed football games and other typical college experiences.
Last weekend, as my friends all went out and my roommates spent the night at rehearsals and other friends' houses, I forced myself to stay home. I knew my body was exhausted, and it was time to stay in and go to sleep early.
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Anyone with information about Zalokar's whereabouts is asked to contact park dispatch at 209-379-1992 or by emailing yose_desk_officer@nps.gov. Officials particularly want to hear from anyone who may have hiked off trail between Merced Lake Trail and Illilouette Merced Pass Trail over the weekend or were in the area of Mount Clark or Mount Starr King.
About 400 certified search-and-rescue personnel from multiple local, state and federal law enforcement agencies as of Monday afternoon and 34 volunteer fire departments as well as private search-and-rescue groups combed the 6,250-acre Moreau Lake State Park for any signs of the missing child, officials said. Drones, bloodhounds and an airboat were deployed in the search.
Hochul said Charlotte was out around dinnertime on Saturday, riding her bike in the campground with friends she considers cousins. She said the fourth-grade girl was doing one last lap around the park alone when she went missing.
The family of the hiker who went missing in Glacier National Park over the weekend say 19-year-old Matthew Read is recovering and receiving treatment after spending several days lost in the wilderness.
Read is a chemical engineering student at Brigham Young University in Utah who was passing through the national park on a trip back east after the end of the semester. He set out to hike the Huckleberry Lookout Trail on Friday afternoon and was reported missing on Sunday. Search and rescue crews began looking for Read that day and located him late Monday night using a thermal scan.
During major events like the Super Bowl, many individuals can go missing, or worse, become victims of human trafficking. Non-profit organization Free International is actively involved in locating missing children during such times.
Officials identified all five people who were killed during severe flash flooding in Upper Makefield Township over the weekend. The following victims were found dead Saturday and Sunday following the flooding of Houghs Creek:
Officials continue to search for Seley's two children -- 9-month-old Conrad and 2-year-old Matilda (Mattie) Sheils -- who both went missing while their mother and grandmother tried to rescue them from the floodwaters.
"We extend our deepest condolences to all the victims' families and friends during this extremely difficult time," Buck said. "It is a sad time for these families, this community, and all of Bucks County as all efforts are focused on finding the missing children."
Also, on Monday, Bucks County's Board of Commissioners signed an emergency disaster declaration that would direct the county's emergency management coordinator to "take all appropriate action needed" to alleviate the effects of the weekend disaster.
Charlotte's family tells CBS 6 the family had been camping at the park since Friday. Charlotte went for a bike ride at 6:15. When she didn't return in ten minutes, her family started looking for her. They reported her missing to police at 6:45 p.m.
My application is in the area of call center traffic forecasting, so data on weekends is (nearly) always missing, which can be nicely handled by zoo. Also, some discrete points may be missing, I just use R's NA for that.
The thing is: all the nice magic of the forecast package, such as eta(), auto.arima() etc, seem to expect plain ts objects, i.e. equispaced time series not containing any missing data. I think real world applications for equispaced-only time series are definitely existent, but - to my opinion - v e r y limited.
You should be very careful when you apply interpolation before further statistical treatment. The choice you do for your interpolation introduces a bias into your data. This is something you definitely want to avoid, as it could alter the quality of your predictions. In my opinion for missing values such as those you mentioned, that are regularly spaced in time and that correspond to a stop in the activities, it might be more correct to leave these days out of your model. In the the little world of your call center (the model you are building about it), it might be better to consider that time simply stopped when it is closed instead of inventing measurements of a non-existing activity. On the other hand the ARIMA model has been statistically built on the assumption that data is equally spaced. As far as I know there is no adaptation of ARIMA to your case. If you are just missing a few measurements on actual working days, you might be forced to use interpolation.
Second, you take your incomplete time series array and, using a loop, fill the values into the correct timeline, according to the limits of your choosing. When you come upon a row where the unit distance is not one (days (units) are missing), you fill in interpolated values.
Now, since this is your function, you can actually chose how to interpolate. For example you decide that if the distance is less than two units, you use a standard linear interpolation. If a week is missing, you do something else and if a certain threshold of missing dates is reached, you give out a warning about the data - really whatever you want to imagine.
The way to go is to use time series methods which handle missing data. For instance, state space methods. Take a look at astsa R package. It comes with an excellent book on time series analysis. This will handle missing data nicely. Matlab now has a similar functionality in ssm package. You have to learn converting your models into state space form, but you have to learn this anyways if you want to step away from auto.arima "magic". 589ccfa754
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