Converting back and forth between different video formats is relatively is easy with GUIs but with command line tools it much streamlined and efficient, not to say it is highly programmable.
Obtain the full location of an ffmpeg build. For example, in windows it could be:
Genetic drift is the result of bernouli process on survival of individuals (given some probability for each of them) of a population over a number of independent trials (Generation).
Apparently there are two techniques of seeing such process – one individual level, other the population level.
A normal function isn’t so normal The normal density function is:
\[ \large f(x) = \frac{1}{\sqrt{2 \pi} \sigma} \exp^{-\frac{(x - \mu)^2}{(2 \sigma^2)}} \]
It doesn’t make sense to calculate the probability for a single value in a continuous probability function, it is by definition zero, but you can calculate relative likelihoods (heights).
Linear mixed models are widely used in Agriculture and Plant Breeding, as of recent. With access to genotype data high resolution phenotype data, it has become more of a requirement to use this family of model.
Mixed models allow for experimental (design or outcome) variables’ parameter estimates to have probabilistic distributions – most commonly normal – with opportunity to specify different variance-covariance components among the levels of those variables.
Correlation Correlation is a bivariate summary statistic. It basically talks of direction and magnitidue of association of two variables. Besides formatting with significance stars, color coding correlation coefficient table might be helpful to pick patterns out in a quick glimpse.
Take a grid and serpentine it row-wise or column-wise This fn joins two matrices alternately columnwise, which is why this is the source of inspiration for generating serpentine design.
alternate.cols <- function(m1, m2) { cbind(m1, m2)[, order(c(seq(ncol(m1)), seq(ncol(m2))))] } A custom function to create a serpentine design in whatever fashion specified:
Background Video editing and format conversion has, up untill recently, been a subject of much domain knowledge. Open source tool ffmpeg is so versatile a toolbox that almost any media file can be tamed to our need.
I got chance to learn more of it’s feature of trimming and merging media files.
SIR model of COVID-19 epidemiology ## # A tibble: 5,555 x 6 ## beta_id time S I R beta_value ## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> ## 1 1 0 0.7 0.02 0.01 3.2 ## 2 1 0.5 0.
Linear model (simple forms) fitting I use mtcars dataset to construct some basic regression models and fit those.
# convert available data to use in fitting mtcars_reg_df <- mtcars %>% rownames_to_column("carnames") %>% as_tibble() %>% mutate_at(c("gear", "am", "vs", "cyl"), as.
Likelihood theory Probit models were the first of those being used to analyze non-normal data using non-linear models. In an early example of probit regression, Bliss(1934) describes an experiment in which nicotine is applied to aphids and the proportion killed is recorded.