qqline r

))> BoxPlot (x$x1, x$x2, x$x3)> BoxPlot (X[2:4], col=c ("Red", "Blue", "green"), notch=t)> Stars (X[c ("x1", "X2", "x3")])> Stars (X[c ("x1", "X2", "x3")],full=t, Draw.segment=t)> Faces (x[c ("x1", "X2", "x3")])> Stem (x$x1)The decimal point was at the |80 | 00000 82 | 0000000 84 | 00000000000 86 | 000000000000 88 | 0000000000000 90 | 0000000000 92 | 000000000000 94 | 00000000 96 | 00000000 98 | 000000000000 100 | 00> Stem (x$x2, scale = 1, width = +, Atom = 1e-08)The decimal point was 1 digit (

I. Start with CSS and Js. Front-end CSS stores all the styles on the website page. Page StyleCodeIt is best to write it here and implement it by calling. It cannot appear in makehtml. php. Front-end JS mainly includes Ajax. JS, check_from.js, JS about jquery, Main. JS, and qqline. js. Ajax. js includes front-end business functions. js functions such as product search, order management, page Jump, and email submission. check_from.js include JS that f

() and pairs () functions draw a scatter chart by default, but you can specify other low-level drawing functions, such as Lines,panel.smooth, with one panel= parameter. Tsplot (x) draws time series graphs. Multiple parameters when Tsplot (x1, x2, ...) To draw multiple curves and automatically unify the range of curve values. If the parameter is not a time series object, the following subscript 1,2,3 is the horizontal coordinate drawing. 6. Qqnorm () normal QQ diagram and Qqplot () two overall Q

. >qqnorm (Cars$speed) >qqline (Cars$speed) 5.5.3 stem and leaf diagramUsing function stem () to draw stem and leaf plots in RStem (x,scale=1,width=80,atom=1e-08)where x is the data vector, the scale controls the length of the stem and leaf graph, width controls the drawing's widths, and atom is the tolerance. > Set.seed (111) > S=sample (cars$speed,25) > Stem (s) The decimal point was 1 digit (s) to the right

Statistical simulation of random number distributions1. What is the central limit theorem. 2. Two distribution simulation Center limit theorem (also known as the Laplace theorem) #首先生成二项分布随机数 m=100;n=10;p=0.25 z Using functions to simulate sim.clt Further understanding of 3.QQ graphs: normal probability graphsHistogram to judge whether random number obeys normal distribution, is to add normal density function curve in the graph to compare the judgmentThe idea of a normal probability graph is

> Plot (x1,x2,+ main= ' two-course performance relationship ', #图标题 + xlab= ' math ', #x轴标签 + ylab= ' Chinese ', #y轴标签 + xlim=c (0,100), #x轴范围 + ylim=c (0,100), #y轴范围 + Xaxs= ' i ', #x轴类型 + yaxs= ' r ', + col= ' red ', #颜色 + pch=19) #点的大小　　> Qqnorm (x1) #测试x1是否是正态分布. A scatter plot > qqline (x1) #上面画出的散点图不能关闭 appears. Draw a straight line, the closer to the line, the more close to the normal distribution.　　> num=seq (1,100) #创建学号 > X1=round (runif (10

(Nile)Ndiffs (Nile)[1] 1DnilePlot (Dnile)#拟合ARIMA模型Library (forecast)FitFitAccuracy (FIT)ME RMSE MAE MPE MAPE MASE ACF1Training set-11.9358 142.8071 112.1752-3.574702 12.93594 0.841824 0.1153593#模型评价Qqnorm (Fit$residuals)Qqline (Fit$residuals)Box.test (fit$residuals,type= "Ljung-box")Box-ljung TestData:fit$residualsx-squared = 1.3711, df = 1, P-value = 0.2416#ARIMA Model PredictionForecast (fit,3)Plot (Forecast (fit,3), xlab= "year", ylab= "annual Fl

= ' QQ plot ') qqline (engel$foodexp, col= ' Red ', lwd=2) The results are as follows:Below is the QQ chartThe results show that the variable y obviously does not obey the normal distribution, but it does not require Y to obey the normal distribution, and the regression of the number of digits is not sensitive to the anomaly value point. Let's continue, for comparison, we still do a mean regression, and then do a decimal regression. #可以直接调用数据框里变量 Att

) library ( lattice) library (splines) library ( Survival) Library ( Formula) Library (hmisc) pay = C (11,19,14,22,14,28,13,81,12,43,11,16,31,16,23,42,22,26,17,22,13,27,180,16 , 43,82,14,11,51,76,28,66,29,14,14,65,37,16,37,35,39,27,14,17,13,38,28,40,85,32, 25,26,16,12,54,40,18,27,16,14,33,29,77,50,19,34 par (Mfrow = C (2,2)) #工作薪水的直方图 hist (pay) # Dot Chart of work pay Dotchart (pay) #工作薪水的箱形图 boxplot (pay,horizontal=t) #工作薪水的Q- q map qqnorm (pay) #线性回归

SETWD ("d:/r/r-data/")Data=read.table ("Salary.txt", header=t)Attach (data)Mean (Salary) #工资的平均值Length (Salary) #数据个数Cumsum (Salary) #累加Salary1=cut (salary,3) #将数据分为三组Table (Salary1)Salary1=cut (Salary,3,labels=c ("Low", "medium", "High")) #给每个组设置标签Table (Salary1)Breakpoints=c (0,30,40,50,60,70)Salary2=cut (salary,breaks=breakpoints) #按区间进行分组Table (Salary2)Pic=function (x) {#写一个存储过程Par (Mfrow=c (2,2)) #绘图区域分割为四部分hist (x) #直方图Dotchart (x) #点图BoxPlot (x) #箱线图Qqnorm (x);

vectors, such as Qqplot (Rpois (50,5), Rnorm (50,5,1)), Qqplot ( DATA2,DATA1).Here we need to add a line to make it easy for us to judge that using the Abline () function can be done, but the function needs to specify the slope and intercept of the line, so we need to do some calculations such as:> Qqp> Abline (LM (qqp$x~qqp$y))First, when using Qqplot (), the returned result contains the X and Y values, which we named Qqp so that the LM () function is then used to extract the two values to fit

% confidence space5.ARIMA predictionsSteps:1. Ensure the timing is smooth2. Find a reasonable model (select a possible P-value or Q-value)3. Fitting the Model4. Evaluating models from the perspective of statistical assumptions and forecast accuracy5. ForecastingLibrary (tseries) plot (Nile)#1. Original sequence differential oncendiffs (Nile) dnilediff (Nile)#2. Post-Differential graphicsplot (Dnile) adf.test (dnile) Acf (dnile) PACF (dnile)# 3. Fitting the ModelFit5 )) fit5accuracy (FIT5)#4. Eva

, Qqline Bi-variate Plot:coplot Tree: Rpart Parallel Coordinates:parallel, Paracoor, Parcoord Heat map, Contour:contour, Filled.contour Other diagrams: Stripplot, Sunflowerplot, Interaction.plot, Matplot, Fourfoldplot,Assocplot, Mosaicplot Saved Chart formats: PDF, PostScript, Win.metafile, JPEG, BMP, PNG 8. Data manipulation Missing value: Na.omit Variable Normalization: Scale Variable transpose: t Sa

naked eye, when the scattered points of the distribution closer to the straight line, the distribution of the sequence is closer to normal distribution. The command is as follows:Qqnorm (X3) qqline (X3)Map columnFinally, we introduce the rich map package features provided by R language, first we need to install the maps package, can be used to draw a beautiful map of the world for us to do social network analysis. Unfortunately, the package does not

sample data is approximate to the normal distribution. Library (CAR) #画出QQ图 PDF (qqplot.pdf) qqnorm (data) #画出与QQ图相对应的直线 (reference line) qqline (data,col= "Red") Dev.off () Guides: Add a straight line to the diagram, which is used for reference, to see if the scatter falls near the line. The line is determined by the two points of the One-fourth-point and Three-fourths-point points, the coordinates of the One-fourth-point coordinate are the One-fou