Publications by Anastasia Bernat
Modeling-M
Winter 2020 Flight Trials: Morphology Modeling Flight Trials Winter 2020 Dataset was conducted from 2/17/2020 - 3/10/2020. Soapberry bugs were flight tested twice for multiple hours in the flight mill and observed from 8 AM to (5-8 PM) each day. No morphological covariates were included for thorax width or body length (just looked at sex, host, a...
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Modeling - MM
Winter 2020 Flight Trials: Mass Modeling Flight Trials Winter 2020 Dataset was conducted from 2/17/2020 - 3/10/2020. Soapberry bugs were flight tested twice for multiple hours in the flight mill and observed from 8 AM to (5-8 PM) each day. Used multivariate (lm) and mixed effect modeling (lmer) to analyze the mass results. All Data Cleaning Data...
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Modeling - YN.short
Winter 2020 Flight Trials: Binomial Flight Modeling Flight Trials Winter 2020 Dataset was conducted from 2/17/2020 - 3/10/2020. Soapberry bugs were flight tested twice for multiple hours in the flight mill and observed from 8 AM to (5-8 PM) each day. Used multivariate (glm) and mixed effect modeling (glmer) to analyze the flight results. All Tri...
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PCAs
Winter 2020 Flight Trials: PCA Flight Trials Winter 2020 Dataset was conducted from 2/17/2020 - 3/10/2020. Soapberry bugs were flight tested twice for multiple hours in the flight mill and observed from 8 AM to (5-8 PM) each day. Size-adjusted CPCA (notes) “Morphological relationships change with overall body size and body size often varies am...
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Tables
Counts Grouped by Sex All Tested F 176 118 M 300 214 Females that Laid Eggs: Females That Didn’t Lay Eggs Females That Laid Eggs Total Females Sample Prop Unique Values 24 94 118 0.797 Grouped by Population Tested Bugs By Pop, Sex, and Trial Type (Unique) Sex Sample Sizes Trial Sample Sizes Population Females Males Tr...
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Flight Summary Stats
Winter 2020 Flight Trials Modeling Y/N Flight Reponse The Data Source Scripts output_col = FALSE # Recommend changing this to TRUE if working in Base R or RStudio, and FALSE if generating an html source("src/clean_flight_data.R") # Script that loads and cleans up the data ## ## Attaching package: 'lubridate' ## The following objects are maske...
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Day 5 - Spatial Stats
Load in the csv file. Then plot the low temperatures at different locations in Maine on January 1st, 2020. What do you notice about the plot? Where is it warmer and where is it cooler? What do the grey dots represent? library(tidyverse) ## ── Attaching packages ───────────────────────────...
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Day 4 - Autoregression
AR, MA Exercises Nile Exploratory Data Analysis Let’s start with a quick warm-up where we explore the Nile dataset. First, load the data and make a plot of the autocorrelation function using the Acf function in the forecast library. Try regenerating the one of the plots on Rick’s 4th slide. There were two: the time series of the Nile Annual ...
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Day 3 - Stationarity
outline: Time series basics: create a (time series) ts object from scratch, read in from files, plot Check stationarity for classical times series models by simulation. Handle non-stationary time series. (The goal is to turn non-stationary time series into stationary time series through a series of filters (e.g. detrending, autocorrelation). Il...
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Day 2 - Logistic Regression (notes)
Logistic Regression Exercises Exploratory Data Analysis We will be working with the Default dataset to explore how we can predict logistic regression. # Load the data library(ISLR) data(Default) Let’s start by examining the data: head(Default) ## default student balance income ## 1 No No 729.5265 44361.625 ## 2 No Ye...
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