LM.fit <- lmer(whole_dif~crithidia*fungicide*poly(pollen.ball.id,2)+(1|colony), data = df) LM.fit2 <- lmer(whole_dif~(crithidia+fungicide+poly(pollen.ball.id,2))^2+(1|colony), data = df) summary(LM.fit2) anova(LM.fit2, LM.fit, test = "Chi") #LM.fit2 fits better emtrends(LM.fit2,pairwise~crithidia, var = "pollen.ball.id", max.degree = 2) emtrends(LM.fit2,pairwise~fungicide, var = "pollen.ball.id", max.degree = 2) pollen.emm <- emmeans(time.quad3, ~crithidia*fungicide*time2) pollen.emm

Regression Model: NVIDIA Corporation Stock Market Report

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This is still underdevelopment

Primera parte, hojas, flores, muestreos(1,2,3,5,7)

Loan approval decision tree