vgam(formula=c$Mortality~c$Group+s(c$Age,df=3),family = binomialff(link = "logitlink"),

data = c)
The vgam function is used for fitting a generalized additive model (GAM) with a binomial family and a logit link function. In this case, the response variable is c$Mortality and the predictor variable is c$Age, which is modeled as a smooth function of the Group variable with 3 degrees of freedom. The data is provided in the c dataframe.

相关问题

ggplot()+ geom_histogram(binwidth = 200,data=data,aes(x=SII,y=..count..),alpha = 0.8,colour="gold3",fill="gold3")+ scale_y_continuous(sec.axis = sec_axis(~./80, name = "HR (95%CI) for 2-year all-cause mortality"))+ geom_line(data=HR, aes(SII,yhat*80), linetype="solid",size=1,alpha = 0.7,colour="steelblue1")+ geom_ribbon(data=HR, aes(SII,ymin = lower*80, ymax = upper*80), alpha = 0.1,fill="blue")+ theme_classic()+ geom_hline(yintercept=1*80, linetype=2,size=1)+ geom_vline(xintercept=570,size=1,linetype=2,color = '#d40e8c')+ geom_vline(xintercept=1010,size=1,linetype=2,color = '#d40e8c')+#查表HR=1对应的age labs(x="Systemic immune-inflammation index", y="Count")+ xlim(0,3500)+ labs(title = " ")+ theme(plot.title = element_text(hjust = 0.5))

这是一段 R 代码，使用 ggplot2 包进行数据可视化。首先使用 geom_histogram 函数绘制直方图，binwidth 参数设置直方图的宽度，data 参数指定数据集，aes 函数设置 x 轴为 SII，y 轴为计数，alpha 参数设置透明度，colour 参数设置边框颜色，fill 参数设置填充颜色。然后使用 scale_y_continuous 函数设置 y 轴的第二个坐标轴，sec.axis 参数指定第二个坐标轴，~./80 表示原坐标轴除以 80，name 参数设置坐标轴名称。接着使用 geom_line 函数绘制折线图，data 参数指定数据集，aes 函数设置 x 轴为 SII，y 轴为 yhat*80，linetype 参数设置线型，size 参数设置线宽，alpha 参数设置透明度，colour 参数设置颜色。使用 geom_ribbon 函数绘制带状图，data 参数指定数据集，aes 函数设置 x 轴为 SII，ymin 参数设置下限，ymax 参数设置上限，alpha 参数设置透明度，fill 参数设置填充颜色。使用 theme_classic 函数设置主题样式，geom_hline 函数绘制水平参考线，yintercept 参数设置纵坐标值，linetype 参数设置线型，size 参数设置线宽度。geom_vline 函数绘制竖直参考线，xintercept 参数设置横坐标值，size 参数设置线宽度，linetype 参数设置线型，color 参数设置颜色。最后使用 labs 函数设置图例和坐标轴标签，xlim 函数设置 x 轴的最小值和最大值，labs 函数设置标题，theme 函数设置主题。

> ggplot()+ + geom_histogram(binwidth = 200,data=data,aes(x=SII,y=..frequency..),alpha = 0.8,colour="gold3",fill="gold3")+ + scale_y_continuous(sec.axis = sec_axis(~.*4000, name = "HR (95%CI) for 2-year all-cause mortality"))+ + geom_line(data=HR, aes(SII,yhat/4000), + linetype="solid",size=1,alpha = 0.7,colour="steelblue1")+ + geom_ribbon(data=HR, + aes(SII,ymin = lower/4000, ymax = upper/4000), + alpha = 0.1,fill="blue")+ + theme_classic()+ + geom_hline(yintercept=1/4000, linetype=2,size=1)+ + geom_vline(xintercept=570,size=1,linetype=2,color = '#d40e8c')+ + geom_vline(xintercept=1000,size=1,linetype=2,color = '#d40e8c')+#查表HR=1对应的age + labs(x="Systemic immune-inflammation index", y="Density")+ + xlim(0,4000)+ + labs(title = " ")+ + theme(plot.title = element_text(hjust = 0.5)) Error in `geom_histogram()`: ! Problem while mapping stat to aesthetics. ℹ Error occurred in the 1st layer. Caused by error in `map_statistic()`: ! Aesthetics must be valid computed stats. ✖ The following aesthetics are invalid: ✖ `y = ..frequency..` ℹ Did you map your stat in the wrong layer? Run `rlang::last_error()` to see where the error occurred. Warning messages: 1: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0. ℹ Please use `linewidth` instead. This warning is displayed once every 8 hours. Call `lifecycle::last_lifecycle_warnings()` to see where this warning was generated. 2: The dot-dot notation (`..frequency..`) was deprecated in ggplot2 3.4.0. ℹ Please use `after_stat(frequency)` instead. This warning is displayed once every 8 hours. Call `lifecycle::last_lifecycle_warnings()` to see where this warning was generated. 3: Removed 70 rows containing non-finite values (`stat_bin()`).

这段代码中出现了一些错误，其中一个是出现了无效的映射。具体而言，`y = ..frequency..` 这个映射是无效的，应该使用 `y = after_stat(frequency)`。另外，也出现了一些警告信息，例如 `size` 映射被弃用了，应该使用 `linewidth`。还有一个警告是有70个行包含了非有限值(`stat_bin()`)。这些问题需要修改才能正常运行代码。