Greetings, Colleagues:
I have several Likert-type ordinal data sets consisting of animal responses
with repeated measures. I was able to implement a CLMM model easily enough with
the package `ordinal`. However, the package does not support repeatability
analyses.
Assuming that I subset my
To begin with, I'm not a fan of cross-posting. However, I posted my question on
Stack Exchange more than two weeks ago, but I have yet to receive a sufficient
answer:
https://stats.stackexchange.com/questions/479600/data-with-ordinal-responses-calculate-icc-assessing-model-fit
Here's what
I am attempting to smooth the jagged paths of animal tracks to determine their
distances with greater accuracy. The data is in the form of (x,y) 2D
coordinates. My end goal is to produce a set of interpolating points whereby
their Cartesian distances are equal to each other. So far, I have been
e interval:
-0.9104585 -0.7407939
sample estimates:
cor
-0.8458024
Salvatore A. Sidoti
PhD Student
Behavioral Ecology
-Original Message-
From: David L Carlson [mailto:dcarl...@tamu.edu]
Sent: Monday, November 14, 2016 11:07 AM
To: Sidoti, Salvatore A. <sidoti...@buckeyemail.osu.ed
ginal Message-
From: Jim Lemon [mailto:drjimle...@gmail.com]
Sent: Sunday, November 13, 2016 3:53 PM
To: Sidoti, Salvatore A. <sidoti...@buckeyemail.osu.edu>; r-help mailing list
<r-help@r-project.org>
Subject: Re: [R] Principle Component Analysis: Ranking Animal Size Based
Let's say I perform 4 measurements on an animal: three are linear measurements
in millimeters and the fourth is its weight in milligrams. So, we have a data
set with mixed units.
Based on these four correlated measurements, I would like to obtain one "score"
or value that describes an
I have some angle data from an animal behavior study that I would like to plot
for publication using ggplot2. What follows is my current workflow with some
example data.
### BEGIN SCRIPT ###
### Create two data frames of random Cartesian coordinates ###
df1 <- data.frame(
x = sample(10, 11,
Greetings!
I have several large data sets of animal movements. Their pauses (zero
magnitude vectors) are of particular interest in addition to the speed
distributions that precede the periods of rest. Here is an example of the kind
of data I am interested in analyzing:
x <-
I have two experimental groups (treatment & control) with 6 sets of
observations nested within each group. The number of observations in each set
is not equal.
How do I set up a such an ANOVA in R?
Thank You!
Salvatore Sidoti
PhD Student
Graduate Teaching Assistant
[[alternative
4 5 6 7 8
159 60 33 16 6 1 2 1
> sum(xy.hex@count >= 3)
[1] 59
-
David L Carlson
Department of Anthropology
Texas A University
College Station, TX 77840-4352
-Original Message-
From: R-help [mailto:r-help-boun...@r-project.org
Greetings!
I have a fairly large dataframe (df) with pathing information in the form of
continuous x,y coordinates:
df$x
df$y
With these data, I would like to:
1. Calculate a set of continuous vectors
2. Determine the angle between each of these vectors (in degrees)
3. Count the number of
Greetings!
Is there a way to count the bins in a hexbin plot that meet certain criteria?
For instance, what if I wanted to count the bins (hexes) that have a datapoint
density of some number x?
Thank you!
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