paquetes

library(dplyr)
library(ggplot2)

base de datos

base de datos de prueba

esta es mi base de datos para mi prueba

vector <- cbind(fecha=c(2020,2021,2022,2023,2024),
                cobertura= c(50,60,68,70,85))

base de datos 2

library(readxl)
Abetos <- read_excel("Abetos.xlsx")
View(Abetos)
Abetos$DBH_SPEI <- as.numeric(Abetos$DBH_SPEI)
## Warning: NAs introducidos por coerción
Abetos$delta_time <- as.numeric(Abetos$delta_time)
## Warning: NAs introducidos por coerción

modelo

modelo <- lm(DBH_SPEI~delta_time, data = Abetos)
summary(modelo)
## 
## Call:
## lm(formula = DBH_SPEI ~ delta_time, data = Abetos)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -21.895  -8.466  -3.074   4.515 146.426 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  28.8543     0.6737   42.83   <2e-16 ***
## delta_time   -0.2320     0.0152  -15.27   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 13.94 on 3278 degrees of freedom
##   (784 observations deleted due to missingness)
## Multiple R-squared:  0.06637,    Adjusted R-squared:  0.06609 
## F-statistic:   233 on 1 and 3278 DF,  p-value: < 2.2e-16
ggplot(Abetos, aes(x=delta_time, y=DBH_SPEI, color = 
                     status))+
  geom_point()+
  theme_classic()
## Warning: Removed 784 rows containing missing values or values outside the scale range
## (`geom_point()`).