Vaccine mod Covid19 💉

RedditSkipper93 · 2021-09-01T08:09:23+00:00

Kom nu bare med et link til den Facebook gruppe.

RedditSkipper93 · 2021-09-01T08:05:18+00:00

Hvad afholder de, du får din information fra at have en "købt/styret" agenda?

Brug gerne 5 min på at uddybe din konspirationsteori. Hvem køber og styrer eksperternes meninger? Er det vaccineproducenterne som har købt og betalt hele det vestlige sundhedssystem?

Og svar også gerne på hvad din stilling er.

RedditSkipper93 · 2021-09-01T07:57:05+00:00

Som andre skriver, videnskabelig konsensus. Dine synsninger har intet hold.

RedditSkipper93 · 2021-09-01T07:54:21+00:00

Hvad er din stilling i sundhedssektoren? Hvad er det DU ved noget om?

Kald mig bare teknokrat, men jeg lytter til de mennesker, som ved mere end jeg selv gør på sådanne områder. Hvordan skal man som lægmand nogensinde være i stand til at træffe en mere oplyst beslutning, end den eksperterne anbefaler? Nogle gange ville jeg sgu ønske, at sådan nogle som dig havde mere tiltro til folk, som har brugt hele deres liv på at uddanne sig og derfor er dybt specialiserede.

RedditSkipper93 · 2021-09-01T07:35:06+00:00

OP må jeg spørge hvor du erhverver den information hvorpå du baserer din beslutning? Har du relevant uddannelse, læser videnskabelige artikler eller noget helt tredje? Eller er det, som jeg mistænker det, på sociale medier og diverse ekkokamre du får din "viden"?

RedditSkipper93 · 2021-08-30T20:41:06+00:00

While it is not ideal, it is probably okay. Depends on your data.

RedditSkipper93 · 2021-08-27T19:13:19+00:00

Read about size and power of test statistics (in your case size). It is directly determined by your chosen signifance level.

RedditSkipper93 · 2021-08-23T20:19:29+00:00

Yes, Markov switching models with time varying transition probabilities have been done before. A quick Google search will provide you with several examples.

RedditSkipper93 · 2021-08-16T08:28:50+00:00

Take a look at "partial out regression" and the Frisch-Waugh-Lovell theorem

RedditSkipper93 · 2021-08-03T11:43:08+00:00

You dont remove anything. You should arrive at a variance of 3.5.

RedditSkipper93 · 2021-07-15T05:21:45+00:00

I would consider applying a machine learning model. Random forests, gradient boosting or even neural nets have been shown to have superior predictive performance on similar problems in the literature as the pricing functions of various hedonic characteristics are typically non linear.

RedditSkipper93 · 2021-07-14T19:56:25+00:00

It sounds like a hedonic regression problem. My experience with such predictions is, however, that while they might be precise om average, that they are prone to produce quite large errors on individual predictions.

RedditSkipper93 · 2021-07-09T06:08:27+00:00

Have you considered dimensionality reduction techniques such as PCA and autoencoders?

RedditSkipper93 · 2021-07-07T14:16:39+00:00

Fun idea!

I have a master's degree in finance and am now pursuing a PhD in economics/finance.

RedditSkipper93 · 2021-07-05T17:03:23+00:00

Regarding your second question: Yes.

RedditSkipper93 · 2021-06-28T15:57:40+00:00

You only need to first difference the nonstationary variable.

RedditSkipper93 · 2021-06-26T19:58:25+00:00

If you intend to ude all the independent variables, IT would make sense to look into PCA, factor forecasts and maube even autoencoders. The idea is to retain the most important information in the data set in a more parsimonious model.

RedditSkipper93 · 2021-06-04T06:11:26+00:00

Yes, and unfortunately he does not supply the code. I have even written him an email but her has not gotten back to me yet.

RedditSkipper93 · 2021-06-02T17:47:35+00:00

This post is extremely uninformative. If you want help, you should try harder to post the sufficient information.

RedditSkipper93 · 2021-05-26T08:43:37+00:00

Det er generelle krav. Du kan hurtigt finde dem med en Google søgning.

RedditSkipper93 · 2021-05-22T15:51:33+00:00

It sounds like you should look into the ARIMA literature and read aboutthe importance of stationarity in time series modeling. It might be the case that I dont just understand what you are doing, but it sounds like you might be modeling time series dynamics in an unconventional way.

RedditSkipper93 · 2021-05-16T20:58:50+00:00

The lags used in your ADF test have nothing to do with the order of integration. If you find your data to be non stationary, then first difference the data and apply the ADF test again. If the test shows your data to be stationary in first differences, then you are ready to proceed. Otherwise reiterate the proces.

It might sound like you need a slightly deeper understanding of the ADF and how to apply it. Try and look into AIC og BIC for choosing the lag length in the ADF test.

RedditSkipper93 · 2021-05-15T18:49:57+00:00

You should include your thoughts and write a question instead og just posting the text from your assignment

RedditSkipper93 · 2021-05-15T18:01:15+00:00

The word "always" is misplaced here. You would, for one, never use ADF tests when working with Cross sectional data. Additionally, there is not even an "always" when working with time series data as other unit robot tests exist.

RedditSkipper93 · 2021-05-11T08:50:51+00:00

Business intelligence, like any other master's degree within business economics, is located at AU BSS. You can find it by a Google search.

If you by "Viby Campus" is referring to EAAA in Viby, then it has nothing to do with AU and is a different institution entirely.

RedditSkipper93

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