factor(x = character(), levels, labels = levels)构造一个因子序列。x为原数据,levels是x中的不同水平,labels是与x中每个水平对应的标签。 x <- c("Man", "Male", "Man", "Lady", "Female")## Map from 4 different values to only two levels:xf<-factor(x,levels=c("Male","Man","Lady"...
factor(x = character(), levels, labels = levels)构造一个因子序列。x为原数据,levels是x中的不同水平,labels是与x中每个水平对应的标签。 x <-c("Man","Male","Man","Lady","Female")##Mapfrom4different values to only two levels:xf <- factor(x, levels =c("Male","Man","Lady","Female...
# score1 makes a batch prediction given clean data(indata), # model object(model_param), and the new name of the variable # that is being predicted score1 <- function(indata, model_param, predVarName) { indata[,"DayOfWeek"] <- factor(indata[,"DayOfWeek"], levels=c("Monday",...
Groundwater levels are gradually declining in basins around the world due to anthropogenic and natural factors.Climate is not the only factor contributing ... K Bera,ME Newcomer,P Banik - 地球化学学报(英文) 被引量: 0发表: 2022年 Ground Search and Rescue (GSAR) Baseline Study Geocoding LP-re...
The Arabidopsis trithorax-like factor ATX1 functions in dehydration stress responses via ABA-dependent and ABA-independent pathways. Plant J. 2011;66(5):735–44. https://doi.org/10.1111/j.1365-313X.2011.04534.x. Article CAS PubMed Google Scholar Sun C, Fang J, Zhao T, Xu B, Zhang F...
Another important factor in the determination of gene-set association scores is whether or not to filter SNPs before performing the analysis. Filtering-based methods restrict the analysis to a subset of SNPs that meet a specific level of association (e.g.,P-value < 5 × 10−5). Different...
After checking the Cronbach’s alpha and average variance extracted (AVE), we confirmed that this factor had no negative effect on our research [98], and was thus retained the project. The sample size of the model is small (less than 300), and the items considered by perspective-taking ...
BiocManager::install("limma")library(''limma'')groups <- factor(c(rep(''A'', 3,), rep(''B'',3)))design <- model.matrix(~ groups + 0)rownames(design) <- colnames(gsva_scores)compareE <- makeContrasts(groupsA-groupsB, levels = design)fit <- lmFit(gsva_scores, design)fit <-...
[62,63,64]. All of this can improve accessibility, reduce costs, decrease pollution, and noise levels; and increase attractiveness to potential users, having a positive impact on society (SIM). This reiterates the importance of the interrelation of conditions in moving towards sustainable urban ...
C datasets from different studies resulted in poor mixing of the Markov Chain Monte Carlo age–depth iterations, as indicated by a Gelman and Rubin reduction factor60 of >1.05. This was addressed by using only 14C dates from ref. 54 in our age–depth models for B8 and B17. Disagreement ...