Displaying 4 results from an estimated 4 matches for "group_size".
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2009 Apr 14
1
mean fold change issues and p values
...(NA, nrow)
mean.na <- rep(NA, nrow)
mean.nb <- rep(NA, nrow)
sig.peak.all = data.norm.test
g_1 = sig_test[1]
g_2 = sig_test[2]
col_s1 = 1; col_s2 = 1;
for(i in 1:group){
if(i < g_1)
col_s1 = col_s1+group_size[i]
if(i < g_2)
col_s2 = col_s2+group_size[i]
}
col_e1 = col_s1+group_size[g_1]-1
col_e2 = col_s2+group_size[g_2]-1
for(i in 1:nrow){
na.int.norm <- rep(0, group_size[g_1])
nb.int.norm <- rep(0, group...
2011 Mar 22
3
stacked bar plot
...searching for a simple solution for a couple of days.
I am interested in finding a tool that allows me to plot a stacked bar plot.
My data set is in the following format:
data<-data.frame(Sex=c("M","F","M","F","F"), Number=c(10,3,1,2,3), Group_size=c(1,1,2,2,2))
I would like to have the factor "Sex" stacked, "Group size" as a Factor on the X axis, and "Number" on the Y axis (summed so that there is only one value for each Sex by Group_size combination).
Many, many thanks for any help you may be able to o...
2022 Oct 16
0
[syzbot] net boot error: WARNING in cpumask_next_wrap
...t_affinity(struct virtnet_info *vi)
0;
cpu = cpumask_first(cpu_online_mask);
+ printk(KERN_ERR "%s +%d : %s cpu %d num %d stride %d stragglers %d\n",
+ __FILE__, __LINE__, __func__, cpu, num_cpu, stride, stragglers);
+
for (i = 0; i < vi->curr_queue_pairs; i++) {
group_size = stride + (i < stragglers ? 1 : 0);
+ printk(KERN_ERR "%s +%d : %s vq %d group_size %d",
+ __FILE__, __LINE__, __func__, i, group_size);
for (j = 0; j < group_size; j++) {
cpumask_set_cpu(cpu, mask);
cpu = cpumask_next_wrap(cpu, cpu_online_mask,
nr_cpu_...
2010 Sep 30
1
AIC for tweedie glm
...es are between 0 and 1, so if I rounded to the nearest integer, I'd lose
a lot of the variation.
Here's my code:
out<-tweedie.profile(PUPAE_PER_SUB~1,p.vec=seq(1.1,1.9,length=9),method="interpolation",do.ci=TRUE,do.smooth=TRUE,do.plot=TRUE)
tweedie1<-glm(GSA_TOTAL_DF_PERSUB~GROUP_SIZE+PERIOD+SITE+PERIOD*GROUP_SIZE,family=tweedie(var.power=out$p.max,link.power=0))
This worked fine, and gave results I expected, but I don't know what the
best method is to evaluate the fit of the model. I am used to using AIC to
compare models. A site search turned up AICtweedie, within the twe...