EXECUTIVE SUMMARY:

- The NUFORC have a network of detectors that are believed to detect
magnetic anomalies associated with UFO's. Almost 2 years of data on
these sightings is now available.
- We analyze the monthly data with an AI s/w that "understands"
something about causal links as well as statistical correlations.
- Culling through 1000s of datasets it finds the most likely causes of
the MADAR sightings are associated with several common UFO "types"
most notably Triangles, as well as even more closely matching major
earthquakes in key regions in central and east Asia as well as ocean
ridges in the NE and SE Pacific.
- Some of these relationships seem to predict more MADAR activity in
subsequent months after certain events; some (in particular
earthquake events) predict less MADAR activity.


In getting the latest couple months of NUFORC's summary sighting data
I noticed their MADAR system now has 20 months of data -- enough to
start getting some interesting patterns.

The MADAR boxes are located across America and are designed to detect
unusual changes in the local magnetic field. While there is no
guarantee whatever caused the change is a UFO, it's believed unusual
flying objects sometimes have significant magnetic fields and
reputedly have affected (either "intentionally" or as part of their
"normal operation") car ignition system and other electrical and
electronic equipment.

The summary data currently looks like:


Year.Month Number of MADAR detections
2020.04 89
2020.12 65
2020.21 48
2020.29 67
2020.38 90
2020.46 57
2020.54 55
2020.62 42
2020.71 50
2020.79 54
2020.88 44
2020.96 37
2021.04 36
2021.12 28
2021.21 33
2021.29 43
2021.38 26
2021.46 22
2021.54 12
2021.62 6 <- incomplete month

The same AI s/w I've used before can now grind through this data and
try to establish a list of "similar looking" datasets of the 10s of
1000s it has on file. The reasoning part of the AI is continually
updated -- well the whole thing is subject to tinkering 24/7 -- and
now tries to deduce which data series -- if found to be significantly
connected with the target it was given -- actually might be due to a
causal link.

The reasoning uses a set of in-built "known causal relationships", a
set of rules that enable other causal relationship to be deduced
(e.g. if A causes B and B causes C then A causes C; if A causes B and
C has similar meta-data to A then C might cause B too) plus other
relationship it learns over time. If it sees a strong statistical link
between A and B many times but A is not know to cause B and the link
can't be deduced then it will add it to the list of possible links. The strength of the link is incremented a little each time; when it passes
a limit it's thereafter "believed" to be a causal link and can be used
in other deductions.

This part of the S/W neatly extracts bogus highly-correlated "suspect"
series from consideration as being causal. E.g. it turns out many
UFO-related things seem to highly correlate with the distance of Pluto
from the sun. But it turns out this is only due to most data being of
such short duration we don't have enough to correlate with a large
sample of Pluto's orbit; many high correlations are caused by
Pluto parameters that slowly increase or slowly decrease over the same
period as changes in a target dataset. Many things falsely match because
they are simply slowly changing -- have a modest trend -- like many of Pluto's parameters. If more data were available to match against a good
chunk of Pluto's 248y orbit it might be found to be uncorrelated.

So with the new "causal filter" in place the s/w goes through its list
of data series and finds the most likely "causes" for the MADAR hits
listed above are:

Suspect Lag Log R2 Beta 90% CI
gavqmongolia 4 y 0.92738793 -0.837399 0.120558
mqnepacrise 4 y 0.87520070 -1.5497 0.316871
gavqchina 4 0.81670900 19.4889 4.75022
gavqbandmag40 4 0.80431245 -69.8693 17.7315
mufo-Triangle 4 0.76624152 0.996401 0.249105
mqmagseq30 4 y 0.75440893 1.23887 0.36368
mqtajikistan 4 0.73884750 39.346 12.6664
mqseg110 4 y 0.66785991 0.073287 0.0279852
mufo-Light 2 0.62905482 0.241974 0.0783983 gavufo-Circle 4 0.62762349 0.486872 0.169748
mufo-Diamond 3 0.61939424 3.98103 1.36208
mqband30 4 0.61693743 2.6062 1.0566
mqsepacrise 3 0.61632600 -19.7465 8.92965

The "Suspect" column is the AI's code for each data series it found to
be causally linked with the MADAR hits. Some of the suspect series
were modified in some ways to improve the robustness of the match or
amplify it. E.g. "m" means the s/w added missing values to a data series (usually the global average of available data in the series). "gav"
is an operation that smooths the data and is analogous to calculating
soil moisture from rainfall -- some of the soil moisture carries over
from the last period and some is due to rainfall in the current period.

The "q" data series relate to major (mag 5+) quakes in various regions.
The "ufo" data series are NUFORC data for particular types of UFO's
(usually determined by the "shape" assigned by curators at NUFORC).

Many other series were also found to be possible suspects (e.g. solar
events of certain types), but the table above is just the "most
likely" or "best explanations".

At the top of the list we find big quakes originating in Mongolia
track more than 90% of the month-to-month changes in MADAR hits. The
beta is -ve. For each quake in Mongolia there are statistically fewer
MADAR hits in 4 months across the 20-m dataset. Each big quake in
Mongolia approx 1/2s the MADAR hit rate in 4m time "for some reason".

Quakes in other regions have a similar effect. Quakes near the NE
Pacific Rise greatly decrease MADAR hits 4m later. Quakes nr the SE
Pacific Rise almost stop MADAR hits 3m later. OTOH quakes in the
Tajikistan region greatly increase MADAR readings 4m later. Some
latitude bands are associated with big increases and some with big
decreases in MADAR readings in subsequent months.

In the past my mental model was that stimuli that increase UFO
activity might be analogous to "home" regions. Hit the hornet nest
with a stick and you get a lot of insects buzzing around. Whereas
stimuli that decrease activity may be "hunting grounds". If a farmer
mows down the wildflowers in a field you are likely to see fewer bees
in the area until they grow again.

Of course mental models can be backwards. Or totally wrong. :)

The other items that seem to rise above all the other 1000s of
possible causal links are several ufo types/shapes.

It seems Triangle is the most likely "cause" of 4-m subsequent MADAR
hits. When Triangle sightings go up or down it seems MADAR sightings
4m later go up or down by around the same number almost 8 times out of
10 over the 20m dataset.

Light, Circle and Diamond ufo types also seem to robustly predict
MADAR readings in 3-4 months time as well. While the betas for these
are mostly less than 1, it seems Diamond types are likely to be
"responsible" for multiple MADAR sightings 3 months after a typical
visual report.

--
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* Origin: www.darkrealms.ca (1:229/2)