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| startTime <- Sys.time() | |
| y<-c(10,8,6,4,2) | |
| x<-c(5,4,3,2,1) | |
| n<-length(y) | |
| toplam=0 | |
| i <- 1 | |
| while (i <= n) { |
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| startTime <- Sys.time() | |
| y<-c(10,8,6,4,2) | |
| x<-c(5,4,3,2,1) | |
| n<-length(y) | |
| toplam=0 | |
| for (i in 1:n) { | |
| diff=y[i]-x[i] |
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| class Log: | |
| global date_time | |
| now = datetime.now() | |
| date_time = now.strftime("%m/%d/%Y, %H:%M:%S") | |
| def __init__(self,severity,message,user): | |
| self.severity=severity |
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| --- | |
| title: "R Notebook" | |
| output: html_notebook | |
| --- | |
| # Chapter 10 Canonical correlation Analysis (CH10 p 539) | |
| Chapter is related to Partitioning the covariance matrix (p73 ch2) .(ABbrevation :kısaltma ) |
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| # Multivariate Statisttics 7.Week Lecture Notes | |
| # Multivariate Multiple Regression Analysis | |
| You can find this topic in the chapter 8 in the book. | |
| 1. Multiple Regression | |
| $$ Y = X\beta +\varepsilon ~~\to \text{Regression Model} $$ |
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| #y=ax+b^ | |
| #y<-matrix(c(12,10,8,11,6,7,2,3,3),nrow=9,ncol=1) | |
| #y | |
| #x<-matrix(0:8,nrow=9,ncol=1) | |
| #x | |
| #b<-solve(t(x)%*%x)%*%t(x)%*%y |
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| #varyans kovaryans matrisi tanımlayalım | |
| Sigma<-matrix(c(19,30,2,12,30,57,5,23,2,5,38,47,12,23,43,68),ncol = 4,byrow = True) | |
| #loading matrix | |
| lodMatrix<-matrix(c(4,1,7,2,-1,6,1,8),ncol = 2,byrow = TRUE) | |
| #loading matrisinin transpozu | |
| TransLodMatrix<-t(lodMatrix) | |
| #matrislerin çarpımı | |
| multiple<-lodMatrix %*% TransLodMatrix | |
| #sigma ile ll' çarpımını çıkarıyoruz | |
| Result=Sigma-multiple |
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| companies1 <- c("BİST100","USD","ALTIN","ISDMR1","ISDMR") | |
| cash1<-c(17626,28650,38122,75699,62652) | |
| cash1<-cash1[order(cash1)] | |
| df1<-data.frame(companies1) | |
| barplot(cash1, names.arg= companies1, | |
| main = "Şirket değerleri",col=rainbow(3) | |
| ,xlab = "Şirket isimleri", ylab = "değeri") |
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| library(reshape2) | |
| library(ggplot2) | |
| #yapılacak işler/görevler | |
| tasks <- c("Literatür taraması", "Veri toplanması", "Veri Analizi", "Rapor ve veri görselleştirmesi") | |
| #görevlerimizi bir dataframe'a aktarıyoruz | |
| dfr <- data.frame( | |
| name = factor(tasks, levels = tasks), | |
| start.date = as.Date(c("2010-08-24", "2010-10-31", "2010-11-01", "2011-02-14")), | |
| end.date = as.Date(c("2010-10-31", "2010-12-14", "2011-02-28", "2011-04-30")), | |
| is.critical = c(TRUE, FALSE, FALSE, TRUE) |
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| public class Friends { | |
| private String Name; | |
| private Friends next; | |
| } | |
| public class Person extends Friends { | |
| private String Name; | |
| private Integer HitCount; | |
| public Friend FriendList; | |
| public Person(String n) { | |
| Name = n; |